Project leaders: Tiffany Knight, Joanne Bennett

Most flowering plants (~87%) rely on pollinators for reproduction (Ollerton et al 2011). Thus pollinator declines could threaten native plant biodiversity, ecosystem stability and food security (Goulson et al. 2015). Pollen supplementation experiments, link plant reproductive fitness to pollination; where a plants reproduction is considered limited by pollen receipt if it produces more seeds when supplemented pollen is added compared to a control plant (Knight et al. 2005).

In 2003 Knight et al. (2005) performed a quantitative meta-analysis of 655 pollen supplementation experiments, finding pollen limitation to be common. However, their study and inferences had a North America and European data bias. In 2015, a repeat meta-analysis synthesized ~3000 experiments incorporating and translating research from China, Brazil and South Africa. However, dataset gaps remain in regions expected to experience rapid global change. For example, high latitude regions (North-eastern Europe, e.g., Russia) predicted to experience high rates of climate change (Serreze et al. 2000) and developing regions (e.g., Central Africa) under-going rapid land-use change (Jetz et al. 2007). Much scientific research in these regions is published in local, languages and journals that are not ISI listed, thus difficult to access for non-residents (Amano et al. 2016).

To overcome these issues we propose to perform a meta-analysis of studies on pollen ecology, published in non- English languages utilizing the 2003 global meta-analysis methods. Information gained will be used to determine the breeding system of plant species’, the magnitude by which plant species are pollen limited, and the environmental and plant traits that correlate with pollen limitation.

Students proficient in languages other than Mandarin, English and Portuguese are encouraged to apply.

Project leaders: Katharina Gerstner, Dylan Craven

Large distributed networks of biological experiments (e.g. Nutrient Network¹, Drought Net², TreeDiv Net³, ZenScience⁴) have been implemented to collect data from a broad range of sites in a consistent manner to allow direct comparisons of relationships among systems around the world. Synthesis across sites, sometimes referred to as 'meta-level' analysis', allows inference about ecological phenomena without worrying about methodological differences. In contrast, meta-analysis offers a subtly different perspective on the outcome of experiments or observational studies. Instead of providing a definitive demonstration of a particular phenomenon, the outcomes of independent research studies, like the primary data from which they are derived, are treated as if they are subject to sampling uncertainties. Whether and how this methodological difference causes biases in the results from data synthesis has not yet been explored.

We will use primary data from standardized forest inventories to study the effect of species richness on standing biomass. In preparation of the course, using the same data we will create scenarios of summary statistics which could have been reported in primary studies of similar but not identical research questions, e.g. some studies are restricted to trees with more than 20 cm dbh others to more than 30 cm dbh. During the course, we will explore how methodological differences affect results from data synthesis using the primary data to fit a null model. To do so, we will use an array of quantitative tools (all using R⁵) that are relevant for data synthesis: linear mixed-effects models, bayesian hierarchical models, and meta-analytical regression models.

¹https://www.nutnet.umn.edu/

²http://www.treedivnet.ugent.be/

³http://www.drought-net.org/

⁴http://zenscience.org/

⁵ e.g. packages ‘lme4’ or ‘nlme’ for linear mixed effects models, ‘metafor’ for traditional meta-analysis, and ‘brms’ for bayesian meta-analysis (https://cran.r-project.org/web/packages/brms/brms.pdf)

Project leaders: Carsten Meyer, Antonin Machac

There is a wide consensus that multiple processes influence species richness across scales. In the proposed project, we will evaluate three broad classes of such processes simultaneously (historical, environmental, and anthropogenic) using the structural equation modeling (SEM) framework. The assessment will be conducted across a range of geographic, temporal, and phylogenetic scales. Specifically, we will test a series of scale-specific hypotheses, involving both direct and indirect effects, using mammals as our model system. We will expect that historical factors (time and past geographic area) directly determine species richness over large scales. These large-scale effects will be moderated by meso-scale effects of climate, energy, productivity, and human land-use. The interrelations between these meso-scale effects are perfectly suited for SEM. SEM models will be constructed across a range of geographic (biomes, grid cells), temporal (Eocene, Anthropocene, Present), and phylogenetic scales (classes, families, species) to illuminate the hypothesized effects on richness across multiple scale dimensions. Even though similar efforts have been often been encouraged, multiscale assessments of the processes that together, both directly and indirectly, govern species richness remain surprisingly scarce. Students then will get an excellent opportunity to employ their newly acquired SEM skills toward the resolution of this question. Our project will hopefully yield a more complete and precise understanding of these effects, which might prove qualitatively different from those reported by studies that examined these effects in isolation.

Project leaders: Nico Eisenhauer, Olga Ferlian, Madhav Thakur

Invasive ecosystem engineers can have disproportionally strong impacts on native ecosystems. Invasive earthworms are a prime example of ecosystem engineers that influence many ecosystems around the world. For instance, invasive earthworms can dramatically alter the physico-chemical characteristics of the soil that were previously earthworm-free. The spatial distribution of soil C and soil N and that of other trace elements progressively change with the introduction of invasive earthworms, mainly due to their feeding and soil mixing activities. However, the current information of invasive earthworm effects on soil physico-chemical characteristics is scattered in the literature. We aim to quantitatively synthesize the effects of invasive earthworms on soil physico-chemical characteristics. With this, we aim to broaden the participants’ knowledge of consequences of earthworm invasion for soil biogeochemical characteristics and ecosystem processes. Furthermore, they will gain skills in carrying out literature search, the evaluation of research data, and application of meta-analysis techniques using R statistical software. Prior to the course, we will organize Skype sessions that will familiarize the participants with the course. During the course, participants will search published studies on earthworm invasion effects on different soil physico-chemical parameters and extend an already existing database created by us with the aim of conducting own meta-analyses. We will provide R codes to perform meta-analyses on the assembled database. Further, we aim to discuss our results with the participants and work together on a joint manuscript. Basic R skills are desirable, but not mandatory.

Participants interested in invasion ecology and biodiversity effects in natural settings are encouraged to apply.

Project leader: Markus Lange

In the terrestrial ecosphere three-third of all organic carbon is stored in soils ¹. The most mobile form of soil carbon is dissolved organic carbon (DOC)². It is highly biodegradable and is a main factor in the formation of soil organic matter in the soil profile. Plant diversity holds a central position in controlling ecosystem functions³ that are relevant for element cycling and soil carbon storage ^4-6. Furthermore, diverse ecosystems are considered to be less vulnerable to environmental changes and disturbances (“Diversity–Stability Hypothesis”⁷). Fluxes and concentrations of DOC are highly dynamic, because they vary strongly among seasons⁸, they are strongly affected by human disturbances ⁹ and also by weather extremes. However, the impact of plant diversity on DOC dynamics its potential to stabilize DOC fluxes and dynamics have been not addressed, yet.

This project aims at revealing the impact of plant diversity on DOC fluxes and DOC concentrations. Based on a comprehensive data set of continuous DOC observations over 14 years from a biodiversity experiment, we will identify how plant diversity influences the seasonal dynamics in DOC concentrations and fluxes, and if higher plant diversity lessens the influence of extreme weather events such as heavy rain or summer drought. Using time series analyses and linear mixed effect models, possible shift in seasonal dynamics as well as break points in the time series will be identified.

References:

1              Lal, R. Soil carbon sequestration impacts on global climate change and food security. Science304, 1623-1627, doi:10.1126/science.1097396 (2004).

2              Jansen, B., Kalbitz, K. & McDowell, W. H. Dissolved Organic Matter: Linking Soils and Aquatic Systems. Vadose Zone Journal13, doi:10.2136/vzj2014.05.0051 (2014).

3              Hooper, D. U. et al. Effects of biodiversity on ecosystem functioning: A consensus of current knowledge. Ecological Monographs75, 3-35, doi:10.1890/04-0922 (2005).

4              De Deyn, G. B. et al. Vegetation composition promotes carbon and nitrogen storage in model grassland communities of contrasting soil fertility. Journal of Ecology97, 864-875, doi:10.1111/j.1365-2745.2009.01536.x (2009).

5              Lange, M. et al. Plant diversity increases soil microbial activity and soil carbon storage. Nature Communications6, doi:10.1038/ncomms7707 (2015).

6              Steinbeiss, S. et al. Plant diversity positively affects short-term soil carbon storage in experimental grasslands. Global Change Biology14, 2937-2949, doi:10.1111/j.1365-2486.2008.01697.x (2008).

7              Chapin, F. S. et al. Consequences of changing biodiversity. Nature405, 234-242, doi:10.1038/35012241 (2000).

8              Don, A. & Schulze, E. D. Controls on fluxes and export of dissolved organic carbon in grasslands with contrasting soil types. Biogeochemistry91, 117-131, doi:10.1007/s10533-008-9263-y (2008).

9              Butman, D. E., Wilson, H. F., Barnes, R. T., Xenopoulos, M. A. & Raymond, P. A. Increased mobilization of aged carbon to rivers by human disturbance. Nature Geoscience8, 112-116, doi:10.1038/ngeo2322 (2015).

Project leader: Stephan Kambach

Human land-use is the main driver for the global decline in biodiversity, also in forests ecosystems that are exploited for timber, food and other products. In this project, we will conduct a global meta-analysis on the effect of different levels of forest-use/forest management intensity on species diversity.  We aim to test if these effects are moderated by i) the area of nearby primary forest, ii) the fragmentation of the surrounding forest, iii) the mobility of the focal species and iv) the diversity index reported for which we hypothesize that in case of positive effects on species richness, community evenness still declines significantly.

Prior to the summer school, participants will receive a list with publications relevant to this meta-analysis that was already compiled during the project “Land-Use-BioDiversity-Ecosystem Services-trade-offs” (funded by SESYNC and led by Prof. Ralf Seppelt) and that will be reviewed by the project leader. In 2-3 google hangout meetings the group will discuss the hypotheses, the process of data extraction and the according coding table. During the summer school, participants will then fill this coding table and use QGIS and R (packages metafor, lme4 and ggplot2) to run mixed-effect meta-analysis models and produce publication-quality figures. Expected outputs of the summer school include a filled coding table, an R script providing analyses and figures as well as a structured manuscript.

Project leaders: Isabel M.D. Rosa, Matthias Schröter, Carlos A. Guerra

Ecosystem services are usually conceptualised as a bridge between biodiversity and human wellbeing along a cascade including ecosystem properties that builds the basis for ecosystem services, from which benefits that increase human well-being are derived. However, biodiversity, ecosystem services and human well-being are mostly studied independently - although evidence for their relation is present and accumulating rapidly (2). This undermines our understanding on the extent and complexity of their interlinkages. It is essential to improve this knowledge, given that existing international policy bodies (e.g. IPBES) focus their mission on this relationship. Harrison et al. (3) performed a literature review on the link between biodiversity and ecosystem services, considering 530 research papers, and addressing different measures of biodiversity and ecosystem services. Understanding of the direction and magnitude of the links between ecosystem services and human well-being is however yet missing. Therefore, in this project, students will use the same set of papers reviewed by Harrison et al. (3) to investigate the relationships between the same group of ecosystem services and selected indicators for human well-being (e.g. economic wealth, physical health) (4, 5). In order to perform a meta-analysis, students will extract information regarding the magnitude and direction of these relationships, as well as regarding the relationships established between biodiversity and ecosystem services (only assessed qualitatively in Harrison et al. (3)). Given that these relations are still poorly studied, a complete meta-analysis may not be possible. In this case, students will either produce a structured systematic review following the example provided by Harrison et al. (3) or conduct a new systematic literature search focussing on the link between ecosystem services and human well-being.

References:

1. Haines-Young, R. and M. Potschin, 2010. The links between biodiversity, ecosystem services and human well-being, in: Raffaelli, D., Frid, C. (Ed.), Ecosystem Ecology: a new synthesis.

Cambridge University Press, Cambridge, pp. 110-139.

2. Cardinale, B. J., et al., 2012. Biodiversity loss and its impact on humanity. Nature. 486, 59–67.

3. Harrison, P.A., etal. 2014. Linkages between biodiversity attributes and ecosystem services: A systematic review. Ecosystem Services 9, 191-203.

4. MA, 2003. Ecosystems and Human Well-Being: A Framework for Assessment. Island Press, Washington D.C.

5. Smith, L.M., Case, J.L., Smith, H.M., Harwell, L.C. and Summers, J.K., 2013. Relating ecoystem services to domains of human well-being: Foundation for a U.S. index. Ecological Indicators 28, 79-90.