How will ecosystem services and biodiversity develop in Bavaria? The interdisciplinary collaborative project BLIZ takes a glance into the future and develops new scenarios for a sustainable management of ecosystems in Bavaria.

BLIZ is a joint project of the Technical University of Munich (TUM), the Julius-Maximilians University of Würzburg (JMU), the University of Regensburg (UR) and the Friedrich-Alexander University of Erlangen-Nuremberg (FAU). 

We investigate the impacts of climate change on ecological systems (ecosystem services and biodiversity) and socio-economic systems (land use development) and their interactions. With the help of computer-based simulation models, we investigate which adaptation strategies lead to a stabilization of these systems and under which circumstances drastic ecological degradation or socio-economic changes (so-called tipping points) can occur.

The aim of the collaborative project is to develop concrete instructions for sustainable management and to assess possible uncertainties. This raises the following research questions:

• Which impacts do climate and land use change have on Bavarian ecosystems?
• What are sustainable social and economic (land use) strategies for Bavaria that could counteract the loss of ecosystem services and biodiversity?
• How can ecological and socio-economic tipping points be avoided?

The methodical approach is (1) to develop and apply dynamic models based on newly collected and existing empirical data, (2) to generate an estimate of the uncertainties and to evaluate this uncertainty economically,
(3) to develop appropriate adaptation and management strategies and (4) to communicate these strategies to stakeholders. 

Global change is a threat to biodiversity, the functioning of ecosystems and the provision of ecosystem services in Bavaria.

To ensure ecosystem services – such as agricultural and forestry productivity, climate regulation, water quality, pollination and carbon storage in soil and biomass, and biodiversity – sustainable management strategies must be developed and operationalised. We investigate how climate change will influence land-use and land management. We evaluate the consequences for biological diversity and ecosystem services in Bavaria.

We apply the ecosystem model LPJ-GUESS to estimate climate-related changes in growth conditions. These results are used in subproject 4 to develop land-use change scenarios. From these scenarios, we derive estimates on biotope- and species-shifts or extinction are derived. For this, we make use of the unique dataset on Bavarian distribution of species and biotopes. In a “big data” approach, these are merged with the land use scenarios. Production functions are generated that relate land use and biodiversity to ecosystem services. Impact maps are generated that identify hotspots of biodiversity and show the danger of ecosystem services tipping over. Based on our results, possible pathways for an climate-adapted management is developed and discussed with different interest groups.

Principal investigator
Prof. Dr. Anja Rammig
Professorship for Land Surface-Atmosphere Interactions
Technical University of Munich
Hans-Carl-von-Carlowitz-Platz 2
85354 Freising
Tel: +49 8161 714768

Climate change already has dramatic impacts on species and communities of species. So far, however, models have often only been used to investigate anthropogenic influences on individual species or on hypothetical communities of species. Therefore, it remains unexplored how climate change affects species communities in natural systems – both terrestrial and aquatic. The diversity and complexity of Bavarian landscapes is particularly suitable for researching how biodiversity reacts to climate and land use change.

In order to understand the potential effects of these interacting factors, the subproject investigates how aquatic and terrestrial species communities in Bavarian lakes and landscapes react to various changes in environmental factors. Spatially explicit niche and agent-based models for interacting plant and animal communities are being developed for this purpose. The simulated interactions between all relevant ecological processes result in the distribution and occurrence of plant and animal species within spatially structured communities. From the model results, biodiversity hotspots relevant to conservation are derived throughout Bavaria and displayed on maps.

Principal investigator
Prof. Dr. Juliano Sarmento Cabral
Ecosystem Modeling, CCTB
Julius-Maximilians-Universität Würzburg
Emil-Fischer-Str. 32
97074 Würzburg
Tel: +49 931 3182667

Climate and land use change result in increased inputs into lakes. This includes loads of suspended and humic substances as well as nutrients that promote algae blooms. Such inputs act directly or indirectly as optically active substances and influence the light available to water plants. This effects aquatic plant communities, which structure aquatic habitats and supply essential functions to the lake ecosystem. Consequently, changes in the composition of aquatic plants will have a significant impact on the overall aquatic biodiversity.

The objectives of subproject 3 are: 

1) to investigate consequences of increased input of optically active substances on the composition of the underwater vegetation and thus on lake biodiversity, 

2) and to determine the threshold values (tipping points) for substance inputs, which lead to significant changes in the underwater vegetation.

In cooperation with subproject 2, the tolerances and preferences of selected aquatic plants (macrophytes) are determined in experiments. On this basis, macrophyte and biodiversity models will be optimised. These studies are based on climate and land use scenarios developed in subprojects 1 and 4. In this way, data for the optimization of biodiversity models will be collected and the predictions of the models confirmed.

Principal investigator
Dr. Uta Raeder
Limnological Research Station Iffeldor
Chair of Aquatic Systems Biology
Technical University of Munich
Hofmark 1-3
82393 Iffeldorf
Tel: +49 8856 81022

We analyze developments in Bavarian land use both in retrospect and looking into the future. The past changes in the Bavarian landscape are being investigated using remote sensing methods. Based on the forecasts of the climate-sensitive ecosystem model LPJ-GUESS (subproject 1) decisions of farmers and foresters on future land use are modeled. We are interested in how farmers and foresters allocate their resources (such as land) to different usage options among others. To estimate the distribution of land use options, modern land use models are employed at the level of representative agricultural model farms or for representative model forest holdings.

The input information for these models could be productivity and its fluctuations, market price developments, crop failures or calamities in the forest. The analysis of conflicting goals, for example conflicts between productivity and biodiversity or multifunctionality, constitute a substantive part of the research approach. The already existing modeling approaches are extended towards optimization under multiple objectives in order to actively integrate ecosystem services or damages to the environment (for example erosion or excessive use of liquid manure) into the optimization process. The results contrast primarily economically driven as well as multifunctional developments (taking into account ecosystem services) of future land use in Bavaria. Alternative land use options (agroforestry, energy wood plantations) are also evaluated.

Principal investigator
Prof. Dr. Thomas Knoke
Institute of Forest Management
Technical University of Munich
Hans-Carl-von-Carlowitz-Platz 2
85354 Freising
Tel: +49 8161 714701

To assess the consequences of mitigation and adaptation strategies, public and private decision-makers need not only detailed forecasts of the most likely impacts of climate change, but also estimates of the uncertainties associated with such forecasts.

Subproject 5 of BLIZ (BayRisk) at the University of Regensburg deals with quantifying uncertainties in model projections. BayRisk will create uncertainty estimates of the ecological models used in BLIZ, using Monte-Carlo simulations and Bayesian statistical methods. The calculated uncertainties are then used in cooperation with the socio-economic subprojects of BLIZ to derive probability distributions and risks for economically relevant parameters. Hence, BayRisk forms a link between the ecological subprojects 1-3 and the socio-economic subprojects 4 & 6. The latter conduct research on land use decisions and the evaluation of risks and options for action.

Principal investigator
Prof. Dr. Florian Hartig
Group for Theoretical Ecology
Faculty of Biology and Pre-Clinical Medicine
University of Regensburg
Universitätsstraße 31
93053 Regensburg
Tel: +49 941 9434316

The rural areas of Bavaria fulfil a variety of functions: They are main production areas for food and animal feed, wood and energy, they have important ecological functions, and make a significant contribution to environment, nature and landscape protection; furthermore, for a large part of the population they constitute spaces for living, economic activities and recreation. Environmental changes, developments of energy and climate policy as well as social and demographic changes pose complex challenges for the rural areas in Bavaria.

What changes will rural areas experience in the future? How will climate change affect multifunctionality? What social demands will be placed on rural areas in Bavaria in the future? Within subproject 6 these questions are addressed by means of a transdisciplinary research approach. Various actors from politics, environment, economy and civil society will be involved to grasp different perspectives on the development of rural areas and to show to what extent climatic changes already play a role in the actors’ practices or in how far these evolutions are anticipated by the actors.

Principal investigator
Prof. Dr. Perdita Pohle
Institute of Geography
Chair for Geography
Friedrich-Alexander-Universität Erlangen Nürnberg
Wetterkreuz 15
91054 Erlangen
Tel: +49 9131 85 22639