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Climate change is expected to exacerbate the current threats to freshwater ecosystems, yet multifaceted studies on the
potential impacts of climate change on freshwater biodiversity at scales that inform management planning are lacking. The aim of this study was to fill this void through the development of a novel framework for assessing climate
change vulnerability tailored to freshwater ecosystems. The three dimensions of climate change vulnerability are as
follows: (i) exposure to climate change, (ii) sensitivity to altered environmental conditions and (iii) resilience potential.
Our vulnerability framework includes 1685 freshwater species of plants, fishes, molluscs, odonates, amphibians, crayfish and turtles alongside key features within and between catchments, such as topography and connectivity. Several
methodologies were used to combine these dimensions across a variety of future climate change models and scenarios. The resulting indices were overlaid to assess the vulnerability of European freshwater ecosystems at the catchment scale (18 783 catchments). The Balkan Lakes Ohrid and Prespa and Mediterranean islands emerge as most
vulnerable to climate change. For the 2030s, we showed a consensus among the applied methods whereby up to 573
lake and river catchments are highly vulnerable to climate change. The anthropogenic disruption of hydrological
habitat connectivity by dams is the major factor reducing climate change resilience. A gap analysis demonstrated that
the current European protected area network covers <25% of the most vulnerable catchments. Practical steps need to
be taken to ensure the persistence of freshwater biodiversity under climate change. Priority should be placed on
enhancing stakeholder cooperation at the major basin scale towards preventing further degradation of freshwater
ecosystems and maintaining connectivity among catchments. The catchments identified as most vulnerable to climate
change provide preliminary targets for development of climate change conservation management and mitigation
strategies.
The distribution of a species along a thermal gradient is commonly approximated by a unimodal response curve, with a characteristic single optimum near the tempera‐ture where a species is most likely to be found, and a decreasing probability of occur‐rence away from the optimum. We aimed at identifying thermal response curves (TRCs) of European freshwater species and evaluating the potential impact of climate warming across species, taxonomic groups, and latitude. We first applied generalized additive models using catchment‐scale global data on distribution ranges of 577 freshwater species native to Europe and four different temperature variables (the current annual mean air/water temperature and the maximum air/water temperature of the warmest month) to describe species TRCs. We then classified TRCs into one of eight curve types and identified spatial patterns in thermal responses. Finally, we in‐tegrated empirical TRCs and the projected geographic distribution of climate warm‐ing to evaluate the effect of rising temperatures on species’ distributions. For the different temperature variables, 390–463 of 577 species (67.6%–80.2%) were char‐acterized by a unimodal TRC. The number of species with a unimodal TRC decreased from central toward northern and southern Europe. Warming tolerance (WT = maxi‐mum temperature of occurrence—preferred temperature) was higher at higher lati‐tudes. Preferred temperature of many species is already exceeded. Rising temperatures will affect most Mediterranean species. We demonstrated that fresh‐water species’ occurrence probabilities are most frequently unimodal. The impact of the global climate warming on species distributions is species and latitude depend‐ent. Among the studied taxonomic groups, rising temperatures will be most detri‐mental to fish. Our findings support the efforts of catchment‐based freshwater management and conservation in the face of global warming.
Unter Enclothed Cognition versteht die Wissenschaft den Einfluss der Kleidung einer Person auf ihre eigenen kognitiven Prozesse. In vergangenen Studien erzielten etwa Pro-band:innen in Arztkitteln höhere Werte bei Konzentrationstests und formell gekleidete Personen beschrieben ihren Charakter mit anderen Adjektiven als Menschen in neutraler Kleidung. Sofern solche intrapersonellen Effekte der eigenen Kleidung auf die mensch-liche Kognition konstant und in verschiedenen Kontexten auftreten sollten, sind sie von Interesse, wann immer Fähigkeiten und Persönlichkeit eines Menschen valide einge-schätzt werden sollen. Dies ist etwa in Personalauswahlverfahren der Fall, weil dort von den Ergebnissen der verwendeten Tests und Fragebögen oft wichtige Personalentschei-dungen abhängen. Um zu untersuchen, inwiefern die Kleidung eines Bewerbers oder ei-ner Bewerberin durch intrapersonelle Effekte die Ergebnisse von Auswahlverfahren be-einflusst, wurde von Mai bis November 2021 ein Laborexperiment mit studentischen 100 Proband:innen im nordwestdeutschen Osnabrück durchgeführt. Dabei wurden die Ver-suchspersonen unter Verhüllung des eigentlichen Studienzwecks entweder einer formel-len (Sakko/Blazer und Hemd/Bluse) oder einer zwanglosen Kleidungskondition (Kapu-zenpullover und Jeans) zugewiesen, in der sie zum Experiment erscheinen sollten. Dort wurden sie verschiedenen Fragebögen und Tests unterzogen. Es zeigte sich weder in der allgemeinen und situationsspezifischen Selbstwirksamkeit noch in Leistungsmotivation, Konzentration und kognitiver Leistung ein Unterschied zwischen formeller und zwang-loser Kleidung. Die vorliegende Arbeit beschreibt den theoretischen Hintergrund und die Methoden der Studie und diskutiert ihre Ergebnisse.
Niche-based species distribution models (SDMs) have become an essential tool in conservation and restoration planning. Given the current threats to freshwater biodiversity, it is of fundamental importance to address scale effects on the performance of niche-based SDMs of freshwater species’ distributions. The scale effects are addressed here in the context of hierarchical catchment ordering, considered as counterpart to coarsening grain-size by increasing grid-cell size. We combine fish occurrence data from the Danube River Basin, the hierarchical catchment ordering and multiple environmental factors representing topographic, climatic and anthropogenic effects to model fish occurrence probability across multiple scales. We focus on 1st to 5th order catchments. The spatial scale (hierarchical catchment order) only marginally influences the mean performance of SDMs, however the uncertainty of the estimates increases with scale. Key predictors and their relative importance are scale and species dependent. Our findings have useful implications for choosing proper species dependent spatial scales for river rehabilitation measures, and for conservation planning in areas where fine grain species data are unavailable.
Model-derived relationships between chlorophyll a (Chl-a) and nutrients and temperature have fundamental implications for understanding complex interactions among water quality measures used for lake classification, yet accuracy comparisons of different approaches are scarce. Here, we (1) compared Chl-a model performances across linear and nonlinear statistical approaches; (2) evaluated single and combined effects of nutrients, depth, and temperature as lake surface water temperature (LSWT) or altitude on Chl-a; and (3) investigated the reliability of the best water quality model across 13 lakes from perialpine and central Balkan mountain regions. Chl-a was modelled using in situ water quality data from 157 European lakes; elevation data and LSWT in situ data were complemented by remote sensing measurements. Nonlinear approaches performed better, implying complex relationships between Chl-a and the explanatory variables. Boosted regression trees, as the best performing approach, accommodated interactions among predictor variables. Chl-a–nutrient relationships were characterized by sigmoidal curves, with total phosphorus having the largest explanatory power for our study region. In comparison with LSWT, utilization of altitude, the often-used temperature surrogate, led to different influence directions but similar predictive performances. These results support utilizing altitude in models for Chl-a predictions. Compared to Chl-a observations, Chl-a predictions of the best performing approach for mountain lakes (oligotrophic–eutrophic) led to minor differences in trophic state categorizations. Our findings suggest that both models with LSWT and altitude are appropriate for water quality predictions of lakes in mountain regions and emphasize the importance of incorporating interactions among variables when facing lake management challenges.
Land cover change is a dynamic phenomenon driven by synergetic biophysical and socioeconomic effects. It involves massive transitions from natural to less natural habitats and thereby threatens ecosystems and the services they provide. To retain intact ecosystems and reduce land cover change to a minimum of natural transition processes, a dense network of protected areas has been established across Europe. However, even protected areas and in particular the zones around protected areas have been shown to undergo land cover changes. The aim of our study was to compare land cover changes in protected areas, non-protected areas, and 1 km buffer zones around protected areas and analyse their relationship to climatic and socioeconomic factors across Europe between 2000 and 2012 based on earth observation data. We investigated land cover flows describing major change processes: urbanisation, afforestation, deforestation, intensification of agriculture, extensification of agriculture, and formation of water bodies. Based on boosted regression trees, we modelled correlations between land cover flows and climatic and socioeconomic factors. The results show that land cover changes were most frequent in 1 km buffer zones around protected areas (3.0% of all buffer areas affected). Overall, land cover changes within protected areas were less frequent than outside, although they still amounted to 18,800 km2 (1.5% of all protected areas) from 2000 to 2012. In some parts of Europe, urbanisation and intensification of agriculture still accounted for up to 25% of land cover changes within protected areas. Modelling revealed meaningful relationships between land cover changes and a combination of influencing factors. Demographic factors (accessibility to cities and population density) were most important for coarse-scale patterns of land cover changes, whereas fine-scale patterns were most related to longitude (representing the general east/west economic gradient) and latitude (representing the north/south climatic gradient).