Potential Current and Future Habitats of Capra ibex in the European Alps: Does Capra ibex really profit from Climate Change?

Climate induced environmental change leads to loss of biodiversity, particularly in rather extreme ecosystems such as the alpine ecosystems in the European Alps (Pauli et al., 2012). Major reasons are the disruption of seasonal synchronization of interdependent ecological processes and trophic interactions, even though abiotic drivers might have been the trigger, but distinguishing biotic from abiotic causes is difficult, since highly spatial and temporal resolute species data is sparse (Post et al., 2008, Büntgen et al., 2014).


Species distribution of butterflies in Wales

Anthrpogenic carbon dioxide emissions are responsible for climate change (IPCC). The theory that species exist within a bioclimate envelope or climate space is well discussed with many examples being modelled (Pearson 2003). It has been suggested by the Environmental Change Insitute (ECI) project Modelling Natural Resource Responses to Climate Change (MONARCH) that among UK species there are potential “winners” and “losers”. It was reported that some butterfly species would be affected in Wales , with potential decreases in Large heath butterflies and increases in Marsh and Pearl-bordered fritillaries (BBC News & MONARCH). Modelling of species distributions of these three butterfly species was undertaken using species occurrence data, current and future climate data, habitat coverage data and morphological data. Results presented show some agreement with the ECI’s MONARCH project: Decrease in Large heath distribution area and increase in Marsh fritillary distribution area. Results for the Marsh fritillary are less conclusive and indicate a possible range shift. The models and therefore results have some limitations, a primary limitation is the unkown effect of climate change on habitats, which is surely important.


Re-introduction of Eurasian Lynx to Scotland

The Wolf, the Eurasian Lynx, the Iberian Lynx, the Brown Bear and the Wolverine are among the largest carnivores that still exist in Europe (http://iucn.org, 2014). Between all of them, we suggest that the reintroduction of the Eurasian Lynx in Scotland should be implemented. This project proposes a method to assess the possibility of the reintroduction of the carnivore Eurasian lynx in Scotland. Weiterlesen

Endangered Emys Orbicularis in Europe: Modelling the future using Species Distribution Models.


Herein, we model the dispersal of the European pond turtle (Emys orbicularis) across Europe using three different species distribution models (SDMs). SDMs are tools to predict the entire or potential spatial distribution of a species. They correlate known occurences with environmental predictor variables in order to estimate potential habitat dispersal.

The European pond turtle is a highly endangered species native to most of Europe (Figure 1). It has been successfully reintroduced to the environment on many occasions, especially in recent years (Bona et al., 2012; Fritz & Chiari, 2013). Applying SDMs potentially identifies adequate nesting sites and/ or habitat connectivity. It possibly yields insight into the future of the entire species, and its International Union for Conservation of Nature (IUCN) status. SDM results are of high importance in the field of conservation. Weiterlesen

Report: Blue Carbon Project in Lamu, Kenya

CO2 is one of the major drivers of the global climate and plays a key role in the process of climate change. Therefore, understanding the mechanism of the global carbon cycle and examining the contributions of different ecosystems in this process is essential. Recently, the focus of attention has widened towards coastal ecosystems, comprising mangroves, saltmarshes and seagrass meadows. These habitats cover only 2% of the worldwide ocean surface. But despite their small extent, they store up to 50% of the overall C that is sequestered by the oceans worldwide. Additionally, C is stored up to 100times faster than in terrestrial ecosystems and sequestration rates (139gC/m²*yr) exceed those of the tropical rainforests by up to 2-4 times.


Tiger reserve in Myanmar

Tigers have been a target of human hunters for centuries and currently the vast majority of tigers poached is for traditional Chinese medicine “cures”. Numbers of tigers have reached a historical low of 3200 animals with only 1000 breeding females in 2010 according to a report by World Conservation Society securing their status of an endangered species (Walston et al., 2010). Tigers are top predators and a flagship species in the areas they inhabit, they require large habitat area, ranging from 10-50 km2 depending on prey availability (Lynam, 2003). In recent years the country in Myanmar there has been a great push for their protection, in 2003 the country created the National Tiger Action Plan (Lynam, 2003) and in 2010 world’s largest tiger reserve was established in Hukaung Valley.


Spatial pattern of white stork migration in Germany

Spatial pattern of white stork migration  in Germany

by Mary Antonette Beroya-Eitner, Lukas Prey, Vadym Sokol
Modelling project for the course „Global Change Impacts on Species Distributions“ within the study program „Global Change Ecology“



The spatial pattern of migration of white storks is dependent on a number environmental conditions. This study aims to investigate the influence of land cover types and different climatic variables on such pattern for three migration stages (forage, roosting and nesting) based on the migration route data of an individual stork tracked by GPS. Corine land cover map and WorldClim data were used for this purpose. Analyses were mainly done in R. Results show that white storks  nest in rural, mainly agricultural areas, but stay in or close to urban areas for roosting and forage during roosting. As regards the influence of the climatic conditions, results reveal that the precipitation of the wettest month is the most important variable for all the different migration stages.  Application of different models yields different prediction maps. In general, the generalized additive model (GAM) tends to identify more potential sites while the random forest tends to identify lesser number of potential sites.


Modelling plant species richness in the Bavarian Forest

Modelling plant species richness of a temperate forest ecosystem in the Bavarian Forest

Global Change Ecology – B7

Lukas Prey

Scope and Methods: Since its establishment, the National Park Bavarian Forest in south-east Germany aimed at protecting the habitat of a multitude of species from nocuous human influences. Yet, it is still discussed in which manner to foster high species richness through national park management. In other places, ecological conditions have to be analysed prior to the declination of nature protection zones. Depending on site conditions, species richness can differ substantially (Fig. 1). In the following, the influence of a number of ecological parameters on the plant species richness is analysed by using data that was collected along the south- facing slope of the Rachel Mountain. 193 different species were counted in 115 study plots in two concentric hexagons with the outer one having a maximum diameter of 8m (Table 2). For species frequency, species were not double-counted within the study plots. Analysis was done in the program R. For a pre-assessment, the influence of the forest structure was examined using LIDAR-data for 36 of the plots. However, only the mean canopy height was found to be significantly correlated with the species richness on a 10% level, yet with a very low R2 (Fig.2 a). It was hypothesized that plant leaf indices as surrogates for the coverage and content of photosynthetic compounds could correlate with species richness through the putative negative influence of shadowing by high canopy vegetation on the generally species-rich herb and shrub layer. Three indices were included in the model: the NDLI as a lignin index, the LCI as a chlorophyll index and the CRI 550 as a carotenoid index (Gitelson et al., 2002). In the case of the NDLI, it was expected to represent the tree cover which also has a crucial influence on shadowing, nutrient competition and growth factor seasonality. A glm was run using 13 explaining variables for species richness. Furthermore due to lack of data for other variables, a spatial subset was used for predicting the potential species richness based on the plant leaf indices.


Potential habitats of African elephants (Loxodonta africana) in the western part of central Africa according to prevalent environmental conditions and anthropogenic influence


Potential habitats of African elephants (Loxodonta africana) in the western part of central Africa according to prevalent environmental conditions and anthropogenic influence

By Marco Brendel, Wanda Graf, Juliana Kehrer

within the module B5 Global Change Impacts on Species Distributions (Masters Program Global Change Ecology)


1.      Introduction

Movement paths by terrestrial herbivores came into focus of recent ecological research, as these animals are globally increasingly threatened. For habitat protection and species conservation their spatial behaviour is an essential factor. In course of this research project the African elephant (Loxodonta africana), one of the main objectives in ecological studies about endangered species, is regarded (Bindi et al. 2011, Dolmia et al. 2007, Grant et al. 2007, DeKnegt et al. 2011, Wall et al. 2012). Populations of the Loxodonta africana can especially be found in the western part of central Africa, where it is severely endangered by poachers hunting for ivory, and faced with a steady loss and fragmentation of its habitats. Several recent cases of illegal killing of the elephants especially in the Dzanga-Ndoki National Park in Central African Republic show the necessity of expanding its security (Wall et al. 2012). On the basis of their current distribution, potential habitats of elephants in the western part of central Africa have been assessed due to prevalent environmental conditions and anthropogenic influence. Their movement behaviour and habitat preferences are defined by a short distance to roads, as elephants use roads as moving corridors (Douglas-Hamilton et al. 2005). Moreover their habitat use increases with proximity to available water (Harris et al. 2008). Their habitats are determined by a low anthropogenic influence and a high proportion of vegetation (Harris et al. 2008). For the species distribution modelling the algorithms “randomForest”, “tree”, as well as “rpart” were utilized in the programming language R!. In a later step the results might be a basis for indentifying new areas of prospective national parks to ensure the survival of the endangered African elephant.


Species distribution modeling of larch in the European Alps in the face of climate change

by Jürgen Knauer and Tobias SiegLarix_decidua

project in Global Change Impacts on Species Distributions, within the study program Global Change Ecology, University of Bayreuth.




Future projections of climate warming propose substantial changes especially in high altitude ecosystems such as the Alps. Especially the tree line regions as climatically-determined ecotones are regarded to react sensitively to altered temperature regimes (Gehrig-Fasel et al. 2007). Potential impacts include structural changes of tree composition, a rise of the alpine tree line, and altered species composition mainly due to rising temperatures, but also due to other climatic as well as edaphic and topographic factors (Gehrig-Fasel et al. 2007; Theurillat & Guisan 2001). The project presented here was an attempt to model the current and projected distribution of larch (Larix decidua) in the Alps using the entropy model MaxEnt and the IPCC-SRES emission scenario A1B for the time periods 2040-2050 and 2070-2080. According to recent findings we expect a distinguishable shift in the distribution of larch towards higher altitudes. The aims of the project were therefore to assess potential altitudinal as well as geographical changes in the distribution of larch over time as a response to climatic and topographic variables.