Workgroup and EcolChange seminar – Ragnar Viikoja about the effect of farming system on wheat nitrogen assimilation genes

Seminar of Chair of Crop Science and Plant Biology and Centre of Excellence EcolChange, Estonian Univ of Life Sciences .

Ragnar Viikoja is a PhD-student in the Estonian University of Life Sciences.

Title of the talk: The Impact of Farming System on the Expression of Wheat Genes Involved in Nitrogen Assimilation

Time: Monday, 21. January 2018 at 14.00

Place: Tartu, Kreutzwaldi 5 – D239 (Metsamaja)

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New publication – Drivers of species richness and community integrity of small forest patches in an agricultural landscape

Text by Krista Takkis

/This blogpost first appeared on JVS Blog on 4th of January 2019 (link to orginal post)/

Small forest patches (up to a few hectares in size) are a common feature in European agricultural landscapes. These patches can be valuable harbours for biodiversity within the generally species-poor agricultural systems with strong human impact. Different natural species and communities can find refuge in these forest patches. Therefore, it is important to understand what determines species richness and composition of small forest patches in agricultural systems. Equally important is to identify what influences forest community integrity in these patches – the general condition and capability of a community to support its normal composition and functioning.

We studied these two questions based on 27 small forest patches in an agricultural system in Estonia in North-East Europe. The patches were dispersed in an old-established agricultural landscape, which had contained mainly karst-related uncultivated formations since early modern agricultural history. We identified the vascular plants growing in each patch and divided the species into four habitat preference groups – forest specialists, forest generalists, grassland specialists and synanthropic species (those mainly found in anthropogenic habitats). We also calculated three indices to study community integrity – the index of Favourable Conservation Status (FSCi; Helm et al. 2015) and two related indices. These indices characterize community condition and the impact of external influences and non-characteristic species on forest communities and enable studying factors that influence community integrity. In our modelling approach, we combined the island biogeographic theory (patch area and isolation effect) with the properties of the surrounding landscape and local environmental conditions within a patch to study comprehensively the different drivers affecting species richness and community integrity.

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Studied forest patches within the agricultural landscape in northeast Estonia. Most of the uncultivated areas in the region are affected by karst formations. Figure from the original paper

Our analyses confirmed the necessity of studying separately species with different habitat preferences, and of incorporating various landscape and environmental factors in a study. Total plant species richness was determined only by patch area, whereas individual habitat preference groups were influenced by different factors, including patch area, landscape composition and environmental factors. Most important factors for different species groups, as well as for forest community integrity, were patch area, the amount of light above the forest understory and soil reaction. Higher-integrity forest patches were identified by larger patch area, lower light conditions and slightly more acidic soils.

Our study highlights the role of small forest patches as refugia for different species and valuable communities, as well as providers of ecosystem services in the generally impoverished agricultural landscapes. Additionally, it illustrates the necessity to use comprehensive models and take into account patch configuration, surrounding landscape composition and local environmental conditions within a patch to fully understand the drivers behind observed patterns. Better understanding of processes and drivers of species richness and community integrity can help us to protect and promote the favourable conditions in small forest patches and thereby improve the conditions for numerous species and the provision of ecosystem services in agricultural systems.

Citation: Takkis, K., Kull, T., Hallikma, T., Jaksi, P., Kaljund, K., Kauer, K., … & Laanisto, L. (2018). Drivers of species richness and community integrity of small forest patches in an agricultural landscape. Journal of Vegetation Science, 29:978–988 (link to full text)

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Effects of patch size, landscape composition and local environment on species richness and community integrity indices. Numbers on the arrows and arrow thickness indicate the importance of predictors (averaged Akaike weights). Figure from the original paper.

 

Abstract:

Questions

Long‐term fragmentation and land use in Europe have created a landscape pattern where small forest patches are embedded among agricultural landscapes. These small forest patches can be one of the few habitats left to maintain the species richness and ecosystem functions within intensively managed agroecosystems. We ask, which factors determine vascular plant species richness, community composition and forest community integrity in small forest patches in an agricultural landscape?

Location

NE Estonia.

Methods

We combine island biogeographic theory (patch area and isolation) with the properties of the surrounding landscape and local environmental conditions within a patch to study the drivers of species richness and community integrity.

Results

Patch area together with local environmental factors (understorey light conditions and soil reaction) determined both species richness and community integrity. Total species richness and forest generalists were related to patch area alone, whereas forest specialists were additionally dependent on patch light conditions. Species richness of grassland specialists in the forest patches increased with the amount of natural habitat in the surrounding landscape, while the presence of synanthropic species was positively related to soil reaction. Forest community integrity was higher in larger, more shaded patches with low soil reaction, which together defined suitable conditions for forest communities and hindered the intrusion of species from other habitats.

Conclusions

Under a suitable set of conditions, encompassing both favourable landscape and local environmental conditions, even small forest patches can provide habitat for both forest and grassland communities in agricultural landscapes. Comprehensive approaches, considering species composition, environment and landscape conditions simultaneously, are needed for making reliable predictions of biodiversity patterns.

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New member – welcome Tana!

Text and ic by Tana Wuyun

Tana welcome IMG_0630

I´m Tana, and I just started my PhD here in Estonian University of Life Sciences. It’s extremely exciting to be back! I mean back in the scientific field, and especially working in the excellent team under the guidance of Professor Ülo Niinemets.

I got my master´s degree of Ecology in 2010, which was 8 years ago. I was working in different field afterwards. First, I was a Sustainability Programs Manager in an international enterprises located near the Great Wall in Beijing, China, for almost 5 years, working on projects that help the businesses become more sustainable After that I became an English training teacher for more than 2 years, and quickly grew to a senior teacher. I knew I would come back eventually, because there’s no doubt that my heart belongs to SCIENCE! So I am really grateful that Estonian University of Life Sciences offered me this great opportunity in Professor Niinemets’s lab!

During the next few years my research will focus on Herbivory of the ‘living Fossils’. I would like to find the keys hidden behind the mystery nature cabins, and really dig into the ancient world, immerse myself into the joy of sciences!

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New publication – Global trait–environment relationships of plant communities

Text by Martin Luther University in Halle via EurekaAlert

/Ed: This new macroecological paper includes Ülo Niinemets as coauthor./

Which plant species grow where, alongside which others – and why? The diversity of global vegetation can be described based on only a few traits from each species. This has been revealed by a research team led by Martin Luther University Halle-Wittenberg (MLU) and the German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig. In a new study published in the scientific journal Nature Ecology & Evolution, they present the world’s first global vegetation database which contains over 1.1 million complete lists of plant species sampled across all Earth’s ecosystems. The database could help better predict the consequences of global climate change.

All plants face the same challenges, whether they are small grasses, shrubs or trees. “For example, they have to find an efficient way to conduct photosynthesis in order to obtain the energy they need. At the same time, they compete with neighbouring plants for limited resources in the soil, like water and nutrients,” explains Professor Helge Bruelheide from the Institute of Biology / Geobotany at MLU and co-director of iDiv.

Currently around 390,000 plant species are known to science. Over time, each species has developed very different traits in reaction to external factors at their location. These include the plant’s size, the thickness and the chemical constituents of its leaves. These properties are also referred to as functional plant traits. “These functional traits directly influence a plant’s ecosystem function, such as how much biomass it produces or how much carbon dioxide it absorbs from the air,” says Bruelheide.

Until now, researchers have primarily investigated different combinations of these functional traits from the perspective of individual plant species. “In reality, however, plant species rarely occur alone; plants live in communities,” says Bruelheide. Therefore, so-called vegetation databases are needed that contain data on all of the plants growing at a specific location. The German Vegetation Reference Database is an example. It is managed at MLU by Dr. Ute Jandt, a member of Helge Bruelheide’s research group. It contains about data on about 200,000 vegetation plots from published and unpublished vegetation studies. Similar databases exist, or are being compiled, in many other countries.

Up until now there has been no database of databases, to compile and harmonize all these different datasets. As a result, the “sPlot” initiative was launched at the iDiv research centre to develop and set up the first global vegetation database, unifying and merging the existing datasets. “sPlot” currently contains more than 1.1 million vegetation lists from every continent, collected over the past decades by hundreds of researchers from all over the world. “Each point in our database is a real place with precise coordinates and information about all the plant species that co-exist there,” explains Bruelheide.

The research group combined this massive dataset with the world’s largest database for plant traits called “TRY” which is also an iDiv database platform. “It has enabled us to answer questions that nobody has been able to tackle before,” Bruelheide continues. The research tested, for instance, to what extent global factors influence the functional traits of plant communities. Contrary to current opinion, they found that temperature and precipitation play a relatively limited role. “Surprisingly, these two macro-factors are not so important. Our analysis shows, for example, that plant communities are not consistently characterised by thinner leaves as the temperature increases – from the Arctic to the tropical rainforest,” says Bruelheide. Instead the researchers found a close tie between climate variables and the phosphorus supply in the leaves, reflected in the ratio between nitrogen and phosphorus content in the leaf, which is an indicator of plants’ nutritional status. For example, the longer the vegetation period, the lower the phosphorus supply – which also affects leaf thickness. Local land use and the interaction of different plants at a specific location have a much greater impact on the functional traits of plant communities. According to Bruelheide, these findings show that future calculations of plant production in a region cannot only be determined on the basis of simplistic temperature-precipitation models.

The study published in Nature Ecology & Evolution is the first of a series of upcoming papers by the “sPlot” consortium. Being available on request to other scientists, the “sPlot” database is disclosing unprecedented opportunities to tackle numerous biodiversity questions at the global scale, including the issues pertaining to the distribution of non-native plant species and the similarities and differences of plant communities across world regions.

Citation: Bruelheide, H., Dengler, J., Purschke, O., Lenoir, J., Jiménez-Alfaro, B…, Niinemets, Ü…., & Hennekens, S. M. (2018). Global trait–environment relationships of plant communities. Nature Ecology and Evolution, https://doi.org/10.1038/s41559-018-0699-8 (link to full text)

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Abstract:

Plant functional traits directly affect ecosystem functions. At the species level, trait combinations depend on trade-offs representing different ecological strategies, but at the community level trait combinations are expected to be decoupled from these trade-offs because different strategies can facilitate co-existence within communities. A key question is to what extent community-level trait composition is globally filtered and how well it is related to global versus local environmental drivers. Here, we perform a global, plot-level analysis of trait–environment relationships, using a database with more than 1.1 million vegetation plots and 26,632 plant species with trait information. Although we found a strong filtering of 17 functional traits, similar climate and soil conditions support communities differing greatly in mean trait values. The two main community trait axes that capture half of the global trait variation (plant stature and resource acquisitiveness) reflect the trade-offs at the species level but are weakly associated with climate and soil conditions at the global scale. Similarly, within-plot trait variation does not vary systematically with macro-environment. Our results indicate that, at fine spatial grain, macro-environmental drivers are much less important for functional trait composition than has been assumed from floristic analyses restricted to co-occurrence in large grid cells. Instead, trait combinations seem to be predominantly filtered by local-scale factors such as disturbance, fine-scale soil conditions, niche partitioning and biotic interactions.

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Ülo Niinemets awarded with honorary doctor title

Text by EMÜ (link)
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Without the robe (pic from here)

Last week, on November 8th, University of Life Sciences professor Ülo Niinemets received the highest recognition from the foreign university as a researcher. The academician was awarded with the honorary doctor titel (Doctor Honoris Causa) of the Aurel Vlaicu University of Arad from the Romanian University.

According to Professor Niinemets, cooperation with the University of Romania has lasted for a long time. “Together we have published nearly fifty articles. In particular with professor Lucian Copolovic, who at the time was a postdoctoral and senior researcher at the University of Life Sciences,” he said.

Certainly, collaboration between the two universities in the future will continue. Niinemets said that now he will focus more on the medical and crop-specific study of secondary metabolism of the plant.

Estonian University of Life Sciences congratulates professor Niinemets!

rumeenia audoktor

With the robe!

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Our workgroup participated in university´s sports competition

Text and pics by Evi Vaino

Every person who likes to be healthy, happy, and experience less stress has to make at least 10 000 steps every day in medium pace (citation missing…). Unfortunately, average office (and lab) working person typically makes only 3000 – 5000 steps, and that is not enough.

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Evi (nr 3755)

In order to bring the numbers up, our university organizes annual competition “Iga kilomeeter loeb!” (Every kilometer counts!) that promotes moving around on foot, without any vehicle. Both the students and employees can participate.

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Steffen

This year plant physiologists took part with a team of four people:
Ülo Niinemets
Steffen Manfred Noe
Beate Regine Noe
Evi Vaino

spordifoto 2018

Beate

Altogether 24 teams with 82 competitors participated, and total of 7309.33 km was covered during the competition. Within 2 weeks, between 15th and 30th of October we covered altogether 673.29 km, and got the third place, although among employees we were the first!

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Ülo (nr 87)

 

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New publication – A methodology to derive global maps of leaf traits using remote sensing and climate data

Text by Lauri Laanisto

We have a lot of robots nowadays. So why not give them fieldwork assignments? It´s not as simple. Remember how much problems Mars rover “Curiosity” has had. And there is no life in Mars! With all the vegetation and animals and destructive humans – no wonder that developing a fully operational field work robot has been a real challenge for people.

Another option is to use “extraterrestrial” robots. We have quite a lot of stuff hovering on the orbit, including remote sensing satellites. But is it possible to measure for example plant traits from satellites? This has been the direction in remote sensing research for quite a while now. And the paper, which is the basis of this blogspot as it includes Ülo as one of the authors, describes one novel way how to get SLA, LNC, LPC, LDMC and other traits from MODIS/Landsat data with spatial resolution of 500 meters.

So – read the paper how to do it! (Or why…)

Citation: Moreno-Martínez, Á., Camps-Valls, G., Kattge, J., Robinson, N., Reichstein, M., van Bodegom, P., … & Niinemets, Ü. (2018). A methodology to derive global maps of leaf traits using remote sensing and climate data. Remote Sensing of Environment, 218, 69-88. (link to full text)

Abstract:

This paper introduces a modular processing chain to derive global high-resolution maps of leaf traits. In particular, we present global maps at 500 m resolution of specific leaf area, leaf dry matter content, leaf nitrogen and phosphorus content per dry mass, and leaf nitrogen/phosphorus ratio. The processing chain exploits machine learning techniques along with optical remote sensing data (MODIS/Landsat) and climate data for gap filling and up-scaling of in-situ measured leaf traits. The chain first uses random forests regression with surrogates to fill gaps in the database (> 45% of missing entries) and maximizes the global representativeness of the trait dataset. Plant species are then aggregated to Plant Functional Types (PFTs). Next, the spatial abundance of PFTs at MODIS resolution (500 m) is calculated using Landsat data (30 m). Based on these PFT abundances, representative trait values are calculated for MODIS pixels with nearby trait data. Finally, different regression algorithms are applied to globally predict trait estimates from these MODIS pixels using remote sensing and climate data. The methods were compared in terms of precision, robustness and efficiency. The best model (random forests regression) shows good precision (normalized RMSE≤ 20%) and goodness of fit (averaged Pearson’s correlation R = 0.78) in any considered trait. Along with the estimated global maps of leaf traits, we provide associated uncertainty estimates derived from the regression models. The process chain is modular, and can easily accommodate new traits, data streams (traits databases and remote sensing data), and methods. The machine learning techniques applied allow attribution of information gain to data input and thus provide the opportunity to understand trait-environment relationships at the plant and ecosystem scales. The new data products – the gap-filled trait matrix, a global map of PFT abundance per MODIS gridcells and the high-resolution global leaf trait maps – are complementary to existing large-scale observations of the land surface and we therefore anticipate substantial contributions to advances in quantifying, understanding and prediction of the Earth system.

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