The „Rothenbuch concept of dead wood and habitat trees“ and its effects on the diversity of structures and biodiversity of beech-forests

In einem ausgedehnten Laubwaldgebiet im Hochspessart (Nordwestbayern, Bezirk Unterfranken) wurde 2006 untersucht, ob sich alte Rot-Buchenbestände, die seit mehr als 15 Jahren nach dem „Rothenbucher Totholz- und Biotopbaumkonzept“ bewirtschaftet werden, hinsichtlich Struktur-, und Artenvielfalt, von vergleichbaren Beständen ohne ein derartiges Konzpt unterscheiden. Qualitätsziele des Konzeptes sind: Schutz von Horstbäumen, Belassen von 10 ökologisch besonders wertvollen Bäumen pro Hektar, Erhalt und Akkumulation von durchschnittlich 10 m3 Totholz (ohne Stockholz und Kronentotholz) ab 20 Zentimeter pro Hektar auf der gesamten Fläche. Die Umsetzung erfolgt nach dem Grundsatz, dass bei der Auswahl jedes zu entnehmenden Altbaums stets zwischen dem zu erwartenden Holzertrag, der waldbaulichen Notwendigkeit und dem ökologischen Wert abzuwägen ist. Der Vergleich erfolgte in Rothenbuch, und in einem unmittelbar angrenzenden Gebiet ohne entsprechendes Konzept bei Altenbuch, in jeweils 30 ein Hektar großen Gitterfeldern sowie in je 25 Probekreisen (0,1 Hektar). Vögel wurden zur Brutzeit im Rahmen einer quantitativen Gitterfeldkartierung erhoben. Xylobionte Käfer wurden mit Hilfe von Kreuzfensterfallen und zeitstandardisierten Handfängen auf je 25 Probekreisen gefangen. Die Mollusken und Holz bewohnenden Pilze wurden auf je 15 Probekreisen durch standardisierte Aufsammlungen erfasst. In Wirtschaftswäldern seltene Strukturen, die zudem meist geklumpt auftreten (stehendes Totholz, Mulmhöhlen- und sonstige Biotopbäume), wurden auf den 60 Hektarrastern, häufigere und regelmäßiger verteilte Strukturen wie Stockholz oder liegendes Totholz wurden in den Probekreisen aufgenommen. Folgende Hypothesen wurden getestet: 1. Das Rothenbucher Totholz- und Biotopbaumkonzept hat bisher keine Auswirkungen auf Quantität und Qualität von liegendem und stehendem Totholz und Biotopbäumen. 2. Das Rothenbucher Totholz- und Biotopbaumkonzept hat bisher keine Auswirkungen auf Abundanzen und Artenreichtum von Indikatorgruppen. 3. Das Rothenbucher Totholz- und Biotopbaumkonzept hat bisher keine Auswirkungen auf Abundanzen und Artenreichtum an Habitat- und Strukturtradition gebundener und gefährdeter Arten. Es konnte kein Unterschied bei der Anzahl von Biotopbäumen in beiden Gebieten festgestellt werden. Signifikante Unterschiede zugunsten von Rothenbuch ergaben sich bei den Mengen an liegendem und stehendem Totholz und dem Angebot an Totholz stärkerer Dimensionen. Es wurden in Rothenbuch signifikant mehr Vogelarten und Individuen als in Altenbuch registriert. Besonders deutlich im Vergleich der Avizönosen war der Unterschied bei Höhlenbrütern, während die Werte für Vogelarten mit Bindung an Holzstrukturen nur einen Trend ergaben. Die Artenindikatoranalyse ergab folgende Arten als signifikant häufiger und stetiger im totholzreicheren Rothenbuch: Mittelspecht, Kohlmeise, Rotkehlchen, Grauspecht, Halsband- und Trauerschnäpper, Sumpfmeise und Mönchsgrasmücke. Nur der Buchfink (der im bayerischen Wirtschaftwald häufigste Vogel) erwies sich als Charakterart für Altenbuch. Die Artenzahl und Abundanzen der Mollusken lag in Rothenbuch signifikant über den Werten von Altenbuch. Auch die Anzahl gefährdeter Weichtierarten und die entsprechenden Individuenzahlen waren in Rothenbuch höher. Bei xylobionten Käferarten wurden in Rothenbuch signifikant höhere Artenzahlen aller Arten und der gefährdeten Arten festgestellt. Auch die Registrierungen und Artenzahlen von Holz bewohnenden Pilzen pro Probekreis lagen in Rothenbuch signifikant höher. Damit konnte gezeigt werden, dass bezüglich der Totholzmengen bereits nach etwa 15 Jahren deutliche Erfolge erzielt werden können. Das Fehlen von Unterschieden bei Biotopbäumen und wichtiger Indikatorarten der übergeordneten Großlandschaft Spessart in den untersuchten Beständen zeigt aber auch, dass ein Zeitraum von 15 Jahren für die Entstehung hochwertiger Biotopbäume nicht ausreicht. Die Dichte der Totholzstrukturen ist noch unzureichend, um den im Spessart reliktär vorhandenen, an Urwaldstrukturen gebundenen xylobionten Arten eine Wiederbesiedlung auf größerer Fläche zu ermöglichen. Inzwischen geht das Schutzkonzept der Bayrischen Staatsforsten (NEFT 2006) konsequent einen Schritt weiter, nämlich das Erreichen einer Gesamttotholzmenge von mindestens 40 m³ Totholz pro Hektar für über 140jährige Buchenbestände und Bestände älter als 180 gänzlich aus der Nutzung zu nehmen.Investigations were performed in the New Red Sandstone region of the High Spessart in north-west Bavaria (Lower Franconia District), which is famous for extensive beech (Fagus sylvatica) forests on historical woodland sites with continuous tradition of broadleaved tree-cover. Under cool-humid and mild-winter upland conditions (submontane/oceanic) the beech achieves its maximum competitive power and tends to form pure stands of acidic beech forest (Luzuloluzuloidis-Fagetum, upland-form). The main goal was to evaluate the effects of the Rothenbuch concept, only 15 years after its implementation, on the diversity of structures and biodiversity. For this purpose mature stands of Beech (located in Rothenbuch) managed according to the guidelines of the concept were compared with conventionally managed stands (located in Altenbuch). Targets of the concept are protection of trees occupied by eyries of tree-breeding birds, retention of at least 10 ecologically valuable trees per hectare, conservation and accumulation of an average 10 m3 dead wood of over 20 centimeters dbh per hectare (excluding stumps and canopy dead wood). Implementation of the concept in forest management follows the principle “before an old tree is removed, a balance must be made between the estimated yield of timber, silvicultural necessity and the trees ecologicalvalue”. In Rothenbuch and Altenbuch 30 grids of 1ha (bird study; rare forest structures with a clustered distribution) and 25 circular plots of 0.1ha (other groups and more frequent structures) were installed. Birds were surveyed at the time of incubation by quantitative grid mapping. Saproxylic beetles were sampled by flight-interception traps and time-based manual capture. Snails and wood-inhabiting fungi were surveyed by standardized collections on 15 of the 25 circular sample plots. Three null hypotheses were tested: (i) Rothenbuch concept has as yet had no effect on quality and quantity of lying and standing deadwood structures and habitat trees (ii) Rothenbuch concept has as yet had no effects on abundances and species richness of floral and faunal species indicator groups (iii) Rothenbuch concept has as yet had no effects on abundances and species richness of endangered species dependent on temporal continuity of tradition in habitats and structures The follow up study revealed no significant differences between the two sites in terms of the quantity of habitat trees (i.e. living trees with mulm- and rot-holes, rotten crown sections and dead knots, crevices etc.). However, we recorded increased deadwood resources at the Rothenbuch site: lying stems, standing snags and larger diameters. Consequently, more bird species and individuals were present there. We found a particularly pronounced difference in hole-nesters, whereas for birds linked to particular wood structures only a trend was observed. According to a species indicator analysis the following sensitive bird species were found to be significantly more frequent and constantly present at Rothenbuch: middle-spotted woodpecker, great tit, redbreast, grey woodpecker, pied and collared flycatcher, marsh tit and blackcap. On the other hand only common chaffinch proved to be a faithful species in Altenbuch. Species numbers and abundances of terrestrial molluscs and saproxylic beetles were also significantly increased at Rothenbuch, including endangered species listed in red-data books. Moreover, higher numbers of species and abundance of wood-inhabiting fungi were recorded. The results correlated with the increased deadwood resources in Rothenbuch. However, the unchanged low numbers of habitat trees and the lack of important indicator species prove that the period of 15 years was not sufficient for the appearance of habitat trees with suitable microstructures. The frequency of deadwood is furthermore still inadequate for a broader re-colonization by the scattered relict species of virgin forest which are considered to be closely associated with primeval structures and features. In the meantime the concept of the Bavarian state forestry organisation (NEFT 2006) has gone one step further in setting a target dead wood volume of at least 40 m3 per hectare for beech stands older than 140 years, and complete removal of stands older than 180 years from utilization

Critical Assessment of Information Extraction Systems in Biology

An increasing number of groups are now working in the area of text mining, focusing on a wide range of problems and applying both statistical and linguistic approaches. However, it is not possible to compare the different approaches, because there are no common standards or evaluation criteria; in addition, the various groups are addressing different problems, often using private datasets. As a result, it is impossible to determine how well the existing systems perform, and particularly what performance level can be expected in real applications. This is similar to the situation in text processing in the late 1980s, prior to the Message Understanding Conferences (MUCs). With the introduction of a common evaluation and standardized evaluation metrics as part of these conferences, it became possible to compare approaches, to identify those techniques that did or did not work and to make progress. This progress has resulted in a common pipeline of processes and a set of shared tools available to the general research community. The field of biology is ripe for a similar experiment. Inspired by this example, the BioLINK group (Biological Literature, Information and Knowledge [1]) is organizing a CASP-like evaluation for the text data-mining community applied to biology. The two main tasks specifically address two major bottlenecks for text mining in biology: (1) the correct detection of gene and protein names in text; and (2) the extraction of functional information related to proteins based on the GO classification system. For further information and participation details, see http://www.pdg.cnb.uam.es/BioLink/BioCreative.eval.htm

Overview of BioCreAtIvE: critical assessment of information extraction for biology

<p>Abstract</p> <p>Background</p> <p>The goal of the first BioCreAtIvE challenge (Critical Assessment of Information Extraction in Biology) was to provide a set of common evaluation tasks to assess the state of the art for text mining applied to biological problems. The results were presented in a workshop held in Granada, Spain March 28–31, 2004. The articles collected in this <it>BMC Bioinformatics </it>supplement entitled "A critical assessment of text mining methods in molecular biology" describe the BioCreAtIvE tasks, systems, results and their independent evaluation.</p> <p>Results</p> <p>BioCreAtIvE focused on two tasks. The first dealt with extraction of gene or protein names from text, and their mapping into standardized gene identifiers for three model organism databases (fly, mouse, yeast). The second task addressed issues of functional annotation, requiring systems to identify specific text passages that supported Gene Ontology annotations for specific proteins, given full text articles.</p> <p>Conclusion</p> <p>The first BioCreAtIvE assessment achieved a high level of international participation (27 groups from 10 countries). The assessment provided state-of-the-art performance results for a basic task (gene name finding and normalization), where the best systems achieved a balanced 80% precision / recall or better, which potentially makes them suitable for real applications in biology. The results for the advanced task (functional annotation from free text) were significantly lower, demonstrating the current limitations of text-mining approaches where knowledge extrapolation and interpretation are required. In addition, an important contribution of BioCreAtIvE has been the creation and release of training and test data sets for both tasks. There are 22 articles in this special issue, including six that provide analyses of results or data quality for the data sets, including a novel inter-annotator consistency assessment for the test set used in task 2.</p

Evaluation of BioCreAtIvE assessment of task 2

<p>Abstract</p> <p>Background</p> <p>Molecular Biology accumulated substantial amounts of data concerning functions of genes and proteins. Information relating to functional descriptions is generally extracted manually from textual data and stored in biological databases to build up annotations for large collections of gene products. Those annotation databases are crucial for the interpretation of large scale analysis approaches using bioinformatics or experimental techniques. Due to the growing accumulation of functional descriptions in biomedical literature the need for text mining tools to facilitate the extraction of such annotations is urgent. In order to make text mining tools useable in real world scenarios, for instance to assist database curators during annotation of protein function, comparisons and evaluations of different approaches on full text articles are needed.</p> <p>Results</p> <p>The Critical Assessment for Information Extraction in Biology (BioCreAtIvE) contest consists of a community wide competition aiming to evaluate different strategies for text mining tools, as applied to biomedical literature. We report on task two which addressed the automatic extraction and assignment of Gene Ontology (GO) annotations of human proteins, using full text articles. The predictions of task 2 are based on triplets of <it>protein – GO term – article passage</it>. The annotation-relevant text passages were returned by the participants and evaluated by expert curators of the GO annotation (GOA) team at the European Institute of Bioinformatics (EBI). Each participant could submit up to three results for each sub-task comprising task 2. In total more than 15,000 individual results were provided by the participants. The curators evaluated in addition to the annotation itself, whether the protein and the GO term were correctly predicted and traceable through the submitted text fragment.</p> <p>Conclusion</p> <p>Concepts provided by GO are currently the most extended set of terms used for annotating gene products, thus they were explored to assess how effectively text mining tools are able to extract those annotations automatically. Although the obtained results are promising, they are still far from reaching the required performance demanded by real world applications. Among the principal difficulties encountered to address the proposed task, were the complex nature of the GO terms and protein names (the large range of variants which are used to express proteins and especially GO terms in free text), and the lack of a standard training set. A range of very different strategies were used to tackle this task. The dataset generated in line with the BioCreative challenge is publicly available and will allow new possibilities for training information extraction methods in the domain of molecular biology.</p

Faster and more diverse de novo molecular optimization with double-loop reinforcement learning using augmented SMILES

Using generative deep learning models and reinforcement learning together can effectively generate new molecules with desired properties. By employing a multi-objective scoring function, thousands of high-scoring molecules can be generated, making this approach useful for drug discovery and material science. However, the application of these methods can be hindered by computationally expensive or time-consuming scoring procedures, particularly when a large number of function calls are required as feedback in the reinforcement learning optimization. Here, we propose the use of double-loop reinforcement learning with simplified molecular line entry system (SMILES) augmentation to improve the efficiency and speed of the optimization. By adding an inner loop that augments the generated SMILES strings to non-canonical SMILES for use in additional reinforcement learning rounds, we can both reuse the scoring calculations on the molecular level, thereby speeding up the learning process, as well as offer additional protection against mode collapse. We find that employing between 5 and 10 augmentation repetitions is optimal for the scoring functions tested and is further associated with an increased diversity in the generated compounds, improved reproducibility of the sampling runs and the generation of molecules of higher similarity to known ligands.Comment: 25 pages and 18 Figures. Supplementary material include