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1. The view of post-mining sites is rapidly changing among ecologists and conservationists, as sensitive restoration using spontaneous succession may turn such sites into biodiversity refuges in human-exploited regions. However, technical reclamation, consisting of covering the sites by topsoil, sowing fast-growing herb mixtures and planting trees, is still commonly adopted. Until now, no multi-taxa study has compared technically reclaimed sites and sites left with spontaneous succession. 2. We sampled communities of vascular plants and 10 arthropod groups in technically reclaimed and spontaneously restored plots in limestone quarries in the Bohemian Karst, Czech Republic. For comparison, we used paired t-tests and multivariate methods, emphasizing red-list status and habitat specialization of individual species. 3. We recorded 692 species of target taxa, with a high proportion of red-listed (10%) and xeric specialist (14%) species, corroborating the great conservation potential of the quarries. 4. Spontaneously restored post-mining sites did not differ in species richness from the technical reclaimed sites but they supported more rare species. The microhabitat cover of leaf litter, herbs and moss, were all directly influenced by the addition of topsoil during reclamation. 5.Synthesis and applications. Our results show that the high conservation potential of limestone quarries could be realized by allowing succession to progress spontaneously with minimal intervention. Given the threat to semi-natural sparsely vegetated habitats in many regions, active restoration measures at post-mining sites should be limited to maintenance of early successional stages, instead of acceleration of succession.

Evidence-based conservation allows the evaluation of both the collateral benefits and the drawbacks of a wide range of human activities, like quarrying. In this study, the community structure of bees and wasps (Hymenoptera:Apocrita) in Central European sandpits was investigated, focusing on the changes caused by quarrying cessation and technical reclamation, as well as on the changes caused by spontaneous succession leading to the increased availability of food resources but also to the loss of the number and size of available bare sand patches. The bees and wasps demonstrated an exceptional ability to colonize the newly emerging sand quarrying areas, and to survive in them unless these were quarried as intensively as to not allow the development of any early successional vegetation. Both active and closed sandpits were found to serve as important regional refuges for the persistence of many rare species. In total, 221 species were detected, 53 of those were red-listed, with two species thought to be regionally extinct. Typically, active quarrying was associated with the presence of Bembecinus tridens , Halictus subauratus , H. maculatus , and Andrena nigroaenea. The list of the species of conservation interest is provided, and so is the detailed analysis of the life-history traits of the species in relation to the presence of bare sand patches, vegetation cover, quarrying intensity, and time elapsed since the formation of each artificial habitat patch. Sandpits as refuges for xerothermophilous and psammophilous hymenopterans are usually completely and irreversibly lost if the current legislature enforcing the technical reclamation over spontaneous or assisted succession is applied in all or most of the post-mining areas.

The aim of this study was to determine the ecological characteristics of vascular plants colonizing serpentine mining waste dumps and quarries in Lower Silesia. The investigated flora was analyzed with regard to species composition, geographical-historical status, life forms, as well as selected ecological factors, such as light and trophic preferences, soil moisture and reaction, value of resistance to increased heavy metals content in the soil, seed dispersal modes and occurrence of mycorrhiza. There were 113 species of vascular plants, belonging to 28 families, found on seven sites in the study. The most numerous families were Asteraceae, Poaceae, Fabaceae and Caryophyllaceae. Only 13% of all plants recorded occurred on at least five of the study sites. The most numerous were species related to dry grassland communities, particularly of the Festuco-Brometea class, which included taxa endangered in the region of Lower Silesia: Avenula pratensis, Salvia pratensis, Festuca valesiaca. Apophytes dominated in the flora of the investigated communities. Hemicryptophytes were the most numerous group and therophytes were also abundant. The serpentine mining waste dumps and querries hosted heliophilous species which prefer mesic or dry habitats moderately poor in nutrients, featuring neutral soil reaction. On two study sites 30% of the flora composition consisted of species that tolerate an increased content of heavy metals in the soil. Anemochoric species were the most numerous with regard to types of seed dispersal. Species with an arbuscular type of mycorrhiza were definitely dominant in the flora of all the study sites, however, the number of nonmycorrhizal species was also relatively high. It was suggested that both the specific characteristics of the habitats from serpentine mining and the vegetation of adjacent areas had a major impact on the flora composition of the communities in the investigated sites.

The global decline in agricultural land has raised concerns regarding the impact on biodiversity. One effective strategy for preventing a decrease in biodiversity is converting abandoned rice fields into wetland biotopes. However, the impact of these changes on plankton communities remains unclear. The objective of this study was to investigate the diversity and distribution of plankton communities in a single rice field located in Kyoto. The specific objective is to clarify which plankton respond to farmland abandonment. Samples were collected every week from May to July over a two‐year period (rice cultivation period in 2022 and post‐abandonment biotope creation in 2023) to determine species composition and environmental variation. As a result, no changes in plankton community structure occurred after biotope formation, as evidenced by the absence of statistically significant changes in the biodiversity index (H′) or the number of plankton taxa. At the genus level, Trinema, Trachelomonas, and Scenedesmus exhibited a response to fluctuations over the two‐year period, despite their low average contribution to community structure. These groups of organisms may be driving subtle changes in community structure and should therefore be considered as indicator species. Subsequent research endeavors will ascertain the true value of biotope formation in abandoned land. This study clarified changes in plankton communities during the first year of fallow in long‐term cultivated paddy fields in Kyoto. These fields were in a fallow state, with no planting, cultivation, or fertilization occurring. When water was introduced at the same time of year as during active use and the fields were converted into biotopes, diversity and species richness remained unchanged, but changes were observed in testate amoebae.

As part of regular bird surveys across various biotopes within the King Abdulaziz Royal Reserve (KARR), including natural and artificial wetlands, two individuals of Calidris melanotos (Vieillot, 1819) were recorded for the first time in Umm Al Thiyabah, a natural wetland in central Saudi Arabia. This record marks the first confirmed occurrence of this species in any national nature reserve in the country, and only the third nationally, following previous reports from Qatif and Abqaiq. The species is rare vagrant in Saudi Arabia.

The analytical evaluation of urban landscapes is a time-consuming and difficult process as it concerns a large number of components in a complex network of interactions. Studies are either very general and superficial, or unidirectional and in-depth based on certain indicators. For this reason, suitability analyses based on analytic hierarchy process (AHP) create an appropriate framework for evaluating multicomponential urban landscapes systematically. The purpose of this research is to establish an important framework for sustainable landscape planning decisions by comparing it with the artificial topography, population density and biotope characteristics evaluated in the context of microclimatic occurrences in urban landscapes. For this purpose, artificial topography was analyzed by means of AHP according to slope–aspect and elevation criteria. These criteria (slope–aspect–elevation) used to evaluate the artificial topography were preferred for having the potential to represent microclimatic formations such as wind corridor, shading and runoff that affect the decisions on urban landscape planning and management significantly. Artificial topography suitability map obtained was compared to biotope types and population density in research area. In regions with high population density topography compliance is low. In appropriate areas, the building and park biotopes attract attention. These findings indicate that green roof-façade systems should be introduced in such areas and ecological balances should be considered in park design. A balanced distribution of building stock gardens influenced the quality of life positively. It was seen that suitability of topography addressed with regard to life quality and microclimatic comfort is inversely proportional to population density. It was determined by evaluating the relationship of artificial topography with urban biotopes that the predominant biotopes in the areas with high suitability of topography such as garden and grove have high ecological value. Artificial surfaces, such as roads and buildings, gain weight in the areas with high population density and unsuitable urban topography. Considering all of these findings, it was concluded that artificial urban topography is an important indicator for interpreting the relationship with habitat-population density and taking decisions on planning and management of urban landscapes which are in a rapid transformation process.

Rock-inhabiting fungi harbour species-rich, poorly differentiated, extremophilic taxa of polyphyletic origin. Their closest relatives are often well-known species from various biotopes with significant pathogenic potential. Speleothems represent a unique rock-dwelling habitat, whose mycobiota are largely unexplored. Isolation of fungi from speleothem biofilm covering bare granite walls in the Kungsträdgården metro station in Stockholm yielded axenic cultures of two distinct black yeast morphotypes. Phylogenetic analyses of DNA sequences from six nuclear loci, ITS, nuc18S and nuc28S rDNA, rpb1, rpb2 and β-tubulin, support their placement in the Chaetothyriales (Ascomycota). They are described as a new genus Bacillicladium with the type species B. lobatum, and a new species Bradymyces graniticola. Bacillicladium is distantly related to the known five chaetothyrialean families and is unique in the Chaetothyriales by variable morphology showing hyphal, meristematic and yeast-like growth in vitro. The nearest relatives of Bacillicladium are recruited among fungi isolated from cardboard-like construction material produced by arboricolous non-attine ants. Their sister relationship is weakly supported by the Maximum likelihood analysis, but strongly supported by Bayesian inference. The genus Bradymyces is placed amidst members of the Trichomeriaceae and is ecologically undefined; it includes an opportunistic animal pathogen while two other species inhabit rock surfaces. ITS rDNA sequences of three species accepted in Bradymyces and other undescribed species and environmental samples were subjected to phylogenetic analysis and in-depth comparative analysis of ITS1 and ITS2 secondary structures in order to study their intraspecific variability. Compensatory base change criterion in the ITS2 secondary structure supported delimitation of species in Bradymyces, which manifest a limited number of phenotypic features useful for species recognition. The role of fungi in the speleothem biofilm and relationships of Bacillicladium and Bradymyces with other members of the Chaetothyriales are discussed.

Background The Bacteria Biotope (BB) task is a biomedical relation extraction (RE) that aims to study the interaction between bacteria and their locations. This task is considered to pertain to fundamental knowledge in applied microbiology. Some previous investigations conducted the study by applying feature-based models; others have presented deep-learning-based models such as convolutional and recurrent neural networks used with the shortest dependency paths (SDPs). Although SDPs contain valuable and concise information, some parts of crucial information that is required to define bacterial location relationships are often neglected. Moreover, the traditional word-embedding used in previous studies may suffer from word ambiguation across linguistic contexts. Results Here, we present a deep learning model for biomedical RE. The model incorporates feature combinations of SDPs and full sentences with various attention mechanisms. We also used pre-trained contextual representations based on domain-specific vocabularies. To assess the model’s robustness, we introduced a mean F1 score on many models using different random seeds. The experiments were conducted on the standard BB corpus in BioNLP-ST’16. Our experimental results revealed that the model performed better (in terms of both maximum and average F1 scores; 60.77% and 57.63%, respectively) compared with other existing models. Conclusions We demonstrated that our proposed contributions to this task can be used to extract rich lexical, syntactic, and semantic features that effectively boost the model’s performance. Moreover, we analyzed the trade-off between precision and recall to choose the proper cut-off to use in real-world applications.

Background We aim to automatically extract species names of bacteria and their locations from webpages. This task is important for exploiting the vast amount of biological knowledge which is expressed in diverse natural language texts and putting this knowledge in databases for easy access by biologists. The task is challenging and the previous results are far below an acceptable level of performance, particularly for extraction of localization relationships. Therefore, we aim to design a new system for such extractions, using the framework of structured machine learning techniques. Results We design a new model for joint extraction of biomedical entities and the localization relationship. Our model is based on a spatial role labeling (SpRL) model designed for spatial understanding of unrestricted text. We extend SpRL to extract discourse level spatial relations in the biomedical domain and apply it on the BioNLP-ST 2013, BB-shared task. We highlight the main differences between general spatial language understanding and spatial information extraction from the scientific text which is the focus of this work. We exploit the text’s structure and discourse level global features. Our model and the designed features substantially improve on the previous systems, achieving an absolute improvement of approximately 57 percent over F1 measure of the best previous system for this task. Conclusions Our experimental results indicate that a joint learning model over all entities and relationships in a document outperforms a model which extracts entities and relationships independently. Our global learning model significantly improves the state-of-the-art results on this task and has a high potential to be adopted in other natural language processing (NLP) tasks in the biomedical domain.

Background Event extraction from the biomedical literature is one of the most actively researched areas in biomedical text mining and natural language processing. However, most approaches have focused on events within single sentence boundaries, and have thus paid much less attention to events spanning multiple sentences. The Bacteria-Biotope event (BB-event) subtask presented in BioNLP Shared Task 2016 is one such example; a significant amount of relations between bacteria and biotope span more than one sentence, but existing systems have treated them as false negatives because labeled data is not sufficiently large enough to model a complex reasoning process using supervised learning frameworks. Results We present an unsupervised method for inferring cross-sentence events by propagating intra-sentence information to adjacent sentences using context trigger expressions that strongly signal the implicit presence of entities of interest. Such expressions can be collected from a large amount of unlabeled plain text based on simple syntactic constraints, helping to overcome the limitation of relying only on a small number of training examples available. The experimental results demonstrate that our unsupervised system extracts cross-sentence events quite well and outperforms all the state-of-the-art supervised systems when combined with existing methods for intra-sentence event extraction. Moreover, our system is also found effective at detecting long-distance intra-sentence events, compared favorably with existing high-dimensional models such as deep neural networks, without any supervised learning techniques. Conclusions Our linguistically motivated inference model is shown to be effective at detecting implicit events that have not been covered by previous work, without relying on training data or curated knowledge bases. Moreover, it also helps to boost the performance of existing systems by allowing them to detect additional cross-sentence events. We believe that the proposed model offers an effective way to infer implicit information beyond sentence boundaries, especially when human-annotated data is not sufficient enough to train a robust supervised system.