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Southern African protected areas (PAs) harbour a great diversity of animals, which represent a large potential for wildlife tourism. In this region, global change is expected to result in vegetation changes, such as bush encroachment and increases in vegetation density. However, little is known on the influence of vegetation structure on wildlife tourists’ wildlife viewing experience and satisfaction. In this study, we collected data on vegetation structure and perceived mammal densities along 196 road transects (each 5 km long) and conducted a social survey with 651 questionnaires across four PAs in three Southern African countries. Our objectives were 1) to assess visitors’ attitude towards vegetation, 2) to test the influence of perceived mammal density and vegetation structure on the easiness to spot animals, and 3) on visitors’ satisfaction during their visit to PAs. Using a Boosted Regression Tree procedure, we found mostly negative non-linear relationships between vegetation density and wildlife tourists’ experience, and positive relationships between perceived mammal densities and wildlife tourists’ experience. In particular, wildlife tourists disliked road transects with high estimates of vegetation density. Similarly, the easiness to spot animals dropped at thresholds of high vegetation density and at perceived mammal densities lower than 46 individuals per road transect. Finally, tourists’ satisfaction declined linearly with vegetation density and dropped at mammal densities smaller than 26 individuals per transect. Our results suggest that vegetation density has important impacts on tourists’ wildlife viewing experience and satisfaction. Hence, the management of PAs in savannah landscapes should consider how tourists perceive these landscapes and their mammal diversity in order to maintain and develop a sustainable wildlife tourism.
The forest, savanna, and grassland biomes, and the transitions between them, are expected to undergo major changes in the future due to global climate change. Dynamic global vegetation models (DGVMs) are very useful for understanding vegetation dynamics under the present climate, and for predicting its changes under future conditions. However, several DGVMs display high uncertainty in predicting vegetation in tropical areas. Here we perform a comparative analysis of three different DGVMs (JSBACH, LPJ-GUESS-SPITFIRE and aDGVM) with regard to their representation of the ecological mechanisms and feedbacks that determine the forest, savanna, and grassland biomes, in an attempt to bridge the knowledge gap between ecology and global modeling. The outcomes of the models, which include different mechanisms, are compared to observed tree cover along a mean annual precipitation gradient in Africa. By drawing on the large number of recent studies that have delivered new insights into the ecology of tropical ecosystems in general, and of savannas in particular, we identify two main mechanisms that need improved representation in the examined DGVMs. The first mechanism includes water limitation to tree growth, and tree–grass competition for water, which are key factors in determining savanna presence in arid and semi-arid areas. The second is a grass–fire feedback, which maintains both forest and savanna presence in mesic areas. Grasses constitute the majority of the fuel load, and at the same time benefit from the openness of the landscape after fires, since they recover faster than trees. Additionally, these two mechanisms are better represented when the models also include tree life stages (adults and seedlings), and distinguish between fire-prone and shade-tolerant forest trees, and fire-resistant and shade-intolerant savanna trees. Including these basic elements could improve the predictive ability of the DGVMs, not only under current climate conditions but also and especially under future scenarios.
Climate change forces many species to move their ranges to higher latitudes or elevations. Resulting immigration or emigration of species might lead to functional changes, e.g., in the trait distribution and composition of ecological assemblages. Here, we combined approaches from biogeography (species distribution models; SDMs) and community ecology (functional diversity) to investigate potential effects of climate-driven range changes on frugivorous bird assemblages along a 3000 m elevational gradient in the tropical Andes. We used SDMs to model current and projected future occurrence probabilities of frugivorous bird species from the lowlands to the tree line. SDM-derived probabilities of occurrence were combined with traits relevant for seed dispersal of fleshy-fruited plants to calculate functional dispersion (FDis; a measure of functional diversity) for current and future bird assemblages. Comparisons of FDis between current and projected future assemblages showed consistent results across four dispersal scenarios, five climate models and two representative concentration pathways. Projections indicated a decrease of FDis in the lowlands, an increase of FDis at lower mid-elevations and little changes at high elevations. This suggests that functional dispersion responds differently to global warming at different elevational levels, likely modifying avian seed dispersal functions and plant regeneration in forest ecosystems along tropical mountains.
Heat stress transcription factors (HSFs) regulate transcriptional response to a large number of environmental influences, such as temperature fluctuations and chemical compound applications. Plant HSFs represent a large and diverse gene family. The HSF members vary substantially both in gene expression patterns and molecular functions. HEATSTER is a web resource for mining, annotating, and analyzing members of the different classes of HSFs in plants. A web-interface allows the identification and class assignment of HSFs, intuitive searches in the database and visualization of conserved motifs, and domains to classify novel HSFs.
Aim: Predicting future changes in species richness in response to climate change is one of the key challenges in biogeography and conservation ecology. Stacked species distribution models (S‐SDMs) are a commonly used tool to predict current and future species richness. Macroecological models (MEMs), regression models with species richness as response variable, are a less computationally intensive alternative to S‐SDMs. Here, we aim to compare the results of two model types (S‐SDMS and MEMs), for the first time for more than 14,000 species across multiple taxa globally, and to trace the uncertainty in future predictions back to the input data and modelling approach used.
Location: Global land, excluding Antarctica.
Taxon: Amphibians, birds and mammals.
Methods: We fitted S‐SDMs and MEMs using a consistent set of bioclimatic variables and model algorithms and conducted species richness predictions under current and future conditions. For the latter, we used four general circulation models (GCMs) under two representative concentration pathways (RCP2.6 and RCP6.0). Predicted species richness was compared between S‐SDMs and MEMs and for current conditions also to extent‐of‐occurrence (EOO) species richness patterns. For future predictions, we quantified the variance in predicted species richness patterns explained by the choice of model type, model algorithm and GCM using hierarchical cluster analysis and variance partitioning.
Results: Under current conditions, species richness predictions from MEMs and S‐SDMs were strongly correlated with EOO‐based species richness. However, both model types over‐predicted areas with low and under‐predicted areas with high species richness. Outputs from MEMs and S‐SDMs were also highly correlated among each other under current and future conditions. The variance between future predictions was mostly explained by model type.
Main conclusions: Both model types were able to reproduce EOO‐based patterns in global terrestrial vertebrate richness, but produce less collinear predictions of future species richness. Model type by far contributes to most of the variation in the different future species richness predictions, indicating that the two model types should not be used interchangeably. Nevertheless, both model types have their justification, as MEMs can also include species with a restricted range, whereas S‐SDMs are useful for looking at potential species‐specific responses.
The paper lists 337 species from Magurski National Park (MNP): 314 lichens, 18 lichenicolous fungi, four saprotrophic fungi and one lichenicolous myxomycete; 112 of them are new for MNP, 75 are reported for the first time for the Beskid Niski Mts, and two are new for Poland. Selected species are accompanied by taxonomic notes and remarks on their distribution in Poland and other Carpathian ranges. First records of Intralichen lichenicola, Burgoa angulosa and Verrucaria policensis and a second record of Epigloea urosperma are given for the whole Carpathian range, and Fuscidea arboricola was recorded for the first time in the Western Carpathians. Halecania viridescens and Mycomicrothelia confusa are new for the Polish Carpathians. The records of Absconditella pauxilla, Collema crispum, Licea parasitica and Rinodina griseosoralifera in MNP are their second known localities for the range. 93 species, mainly rare or threatened in Poland, were reported from MNP in the 20th century but were not refound.
Background: The current taxonomy of the African giraffe (Giraffa camelopardalis) is primarily based on pelage pattern and geographic distribution, and nine subspecies are currently recognized. Although genetic studies have been conducted, their resolution is low, mainly due to limited sampling. Detailed knowledge about the genetic variation and phylogeography of the South African giraffe (G. c. giraffa) and the Angolan giraffe (G. c. angolensis) is lacking. We investigate genetic variation among giraffe matrilines by increased sampling, with a focus on giraffe key areas in southern Africa.
Results: The 1,562 nucleotides long mitochondrial DNA dataset (cytochrome b and partial control region) comprises 138 parsimony informative sites among 161 giraffe individuals from eight populations. We additionally included two okapis as an outgroup. The analyses of the maternally inherited sequences reveal a deep divergence between northern and southern giraffe populations in Africa, and a general pattern of distinct matrilineal clades corresponding to their geographic distribution. Divergence time estimates among giraffe populations place the deepest splits at several hundred thousand years ago.
Conclusions: Our increased sampling in southern Africa suggests that the distribution ranges of the Angolan and South African giraffe need to be redefined. Knowledge about the phylogeography and genetic variation of these two maternal lineages is crucial for the development of appropriate management strategies.
An individual's choices are shaped by its experience, a fundamental property of behavior important to understanding complex processes. Learning and memory are observed across many taxa and can drive behaviors, including foraging behavior. To explore the conditions under which memory provides an advantage, we present a continuous-space, continuous-time model of animal movement that incorporates learning and memory. Using simulation models, we evaluate the benefit memory provides across several types of landscapes with variable-quality resources and compare the memory model within a nested hierarchy of simpler models (behavioral switching and random walk). We find that memory almost always leads to improved foraging success, but that this effect is most marked in landscapes containing sparse, contiguous patches of high-value resources that regenerate relatively fast and are located in an otherwise devoid landscape. In these cases, there is a large payoff for finding a resource patch, due to size, value, or locational difficulty. While memory-informed search is difficult to differentiate from other factors using solely movement data, our results suggest that disproportionate spatial use of higher value areas, higher consumption rates, and consumption variability all point to memory influencing the movement direction of animals in certain ecosystems.
Menschliche Aktivitäten beeinflussen beinahe alle Bereiche des Lebens auf der Erde (MEA 2005a; UNEP 2007). Die Zerstörung und Veränderung natürlicher Lebensräume sind als Hauptursache für den weltweiten Biodiversitätsverlust identifiziert (Harrison and Bruna 1999; Dale et al. 2000; Foley et al. 2005; MEA 2005a). Zusammen mit dem Klimawandel wird die Landnutzungsveränderung daher als einflussreichster Aspekt anthropogen verursachten globalen Wandels betrachtet (MEA 2005a). Landnutzungsveränderung schließt sowohl die Umwandlung natürlicher Habitate in Agrarland oder Siedlungen als auch die Landnutzungsintensivierung in bereits kultivierten Landschaften mit ein. Diese Veränderungen haben weitreichende Konsequenzen für die Artenvielfalt und resultieren häufig in dem Verlust von Arten mit zunehmender Intensität der Landnutzung (Scholes and Biggs 2005).
Biodiversität und Ökosysteme stellen viele verschiedene Funktionen zur Verfügung, wie z. B. die Sauerstoffproduktion, die Reinigung von Wasser und die Bestäubung von Nutzpflanzen.
Einige dieser Funktionen sind hilfreich, andere wichtig und wieder andere notwendig für das menschliche Wohlergehen (MEA 2005b; UNEP 2007). Mittlerweile sind Ökosystemfunktionen und die vielen Nutzen, die sie erbringen, zu einem zentralen Thema der interdisziplinären Forschung von Sozialwissenschaften und Naturwissenschaften geworden (Barkmann et al. 2008 und darin enthaltene Referenzen). Dadurch bedingt ist es zu einiger Verwirrung bezüglich der verwendeten Begriffe der "Ökosystemfunktion" (engl. "ecosystem function") und dem der "Ökosystemdienstleistung" (engl. "ecosystem service") gekommen (deGroot et al. 2002). Da der Fokus meiner Arbeit auf grundlegenden Funktionen von Ökosystemen liegt, verwende ich im Folgenden den Begriff der Ökosystemfunktion.
Für viele Ökosystemfunktionen ist noch sehr unzureichend bekannt, wie diese von externen Störungen beeinflusst werden (Kremen and Ostfeld 2005; Balvanera et al. 2006). Ökosystemfunktionen werden selten von nur einer einzigen Art aufrechterhalten, sondern meist von einer ganzen Reihe unterschiedlicher taxonomischer Gruppen – alle mit ihren ganz eigenen Ansprüchen. Diese Arten, wie auch deren intra- und interspezifischen Interaktionen, können durchaus nterschiedlich auf die gleiche Störungsquelle oder Störungsintensität reagieren. Dies kann Vorhersagen zum Verhalten von Ökosystemfunktionen extrem erschweren. ...
Diatoms are thought to provide about 40% of total global photosynthesis and diatoms of the genus Coscinodiscus are an important, sometimes dominant, cosmopolitan component of the marine diatom community. The oomycete parasitoid Lagenisma coscinodisci is widespread in the northern hemisphere on its hosts in the genus Coscinodiscus. Because of its potential ecological importance, it would be a suitable pathogen model to investigate plankton/parasite interactions, but the species cannot be cultivated on media without its host, so far. Thus, it was the aim of this study to explore the potential of dual culture of host and pathogen in the laboratory and to optimise cultivation to ensure a long-term cultivation of the pathogen. Here, we report successful cultivation of a single spore strain of L. coscinodisci (Isla), on several Coscinodiscus species and strains, as well as the establishment of a cultivation routine with Coscinodiscus granii (CGS1 and CG36), which enabled us to maintain the single spore strain for more than 3 years in 6 cm Petri dishes and 10 ml tissue culture flasks. This opens up the opportunity to study the processes and mechanism in plankton/parasitoid interactions under controlled conditions.