Search

Transcription activator-like (TAL) effectors are injected into host plant cells by Xanthomonas bacteria to function as transcriptional activators for the benefit of the pathogen. The DNA binding domain of TAL effectors is composed of conserved amino acid repeat structures containing repeat-variable diresidues (RVDs) that determine DNA binding specificity. In this paper, we present TALgetter, a new approach for predicting TAL effector target sites based on a statistical model. In contrast to previous approaches, the parameters of TALgetter are estimated from training data computationally. We demonstrate that TALgetter successfully predicts known TAL effector target sites and often yields a greater number of predictions that are consistent with up-regulation in gene expression microarrays than an existing approach, Target Finder of the TALE-NT suite. We study the binding specificities estimated by TALgetter and approve that different RVDs are differently important for transcriptional activation. In subsequent studies, the predictions of TALgetter indicate a previously unreported positional preference of TAL effector target sites relative to the transcription start site. In addition, several TAL effectors are predicted to bind to the TATA-box, which might constitute one general mode of transcriptional activation by TAL effectors. Scrutinizing the predicted target sites of TALgetter, we propose several novel TAL effector virulence targets in rice and sweet orange. TAL-mediated induction of the candidates is supported by gene expression microarrays. Validity of these targets is also supported by functional analogy to known TAL effector targets, by an over-representation of TAL effector targets with similar function, or by a biological function related to pathogen infection. Hence, these predicted TAL effector virulence targets are promising candidates for studying the virulence function of TAL effectors. TALgetter is implemented as part of the open-source Java library Jstacs, and is freely available as a web-application and a command line program. [ABSTRACT FROM AUTHOR]

Carbon storage and catchment hydrology are influenced both by land use changes and climatic changes, but there are few studies addressing both responses under both driving forces. We investigated the relative importance of climate change vs. land use change for four Alpine catchments using the LPJ-GUESS model. Two scenarios of grassland management were calibrated based on the more detailed model PROGRASS. The simulations until 2100 show that only reforestation could lead to an increase of carbon storage under climatic change, whereby a cessation of carbon accumulation occurred in all catchments after 2050. The initial increase in carbon storage was attributable mainly to forest re-growth on abandoned land, whereas the stagnation and decline in the second half of the century was mainly driven by climate change. If land was used more intensively, i.e. as grassland, litter input to the soil decreased due to harvesting, resulting in a decline of soil carbon storage (1.2−2.9 kg C m) that was larger than the climate-induced change (0.8-1.4 kg C m). Land use change influenced transpiration both directly and in interaction with climate change. The response of forested catchments diverged with climatic change (11-40 mm increase in AET), reflecting the differences in forest age, topography and water holding capacity within and between catchments. For grass-dominated catchments, however, transpiration responded in a similar manner to climate change (light management: 23-32 mm AET decrease, heavy management: 29-44 mm AET decrease), likely because grassroots are concentrated in the uppermost soil layers. Both the water and the carbon cycle were more strongly influenced by land use compared to climatic changes, as land use had not only a direct effect on carbon storage and transpiration, but also an indirect effect by modifying the climate change response of transpiration and carbon flux in the catchments. For the carbon cycle, climate change led to a cessation of the catchment response (sink/source strength is limited), whereas for the water cycle, the effect of land use change remains evident throughout the simulation period (changes in evapotranspiration do not attenuate). Thus we conclude that management will have a large potential to influence the carbon and water cycle, which needs to be considered in management planning as well as in climate and hydrological modelling. [ABSTRACT FROM AUTHOR]

Knowledge on the natural dynamics of Norway spruce-European silver fir forests is scarce, but is of high importance for the sustainable management of these ecosystems. Using a unique data set from five forest reserves in the Swiss Alps that covers up to 35 years, we elucidated communalities and differences in stand structure and species composition across the reserves and over time and investigated the role of site conditions versus intrinsic forest dynamics. For the early and late successional phases, we found a clear relationship between stand structure (diameter distributions) and species composition. Two pathways of early succession were evident as a function of the disturbance regime. Thus, the spatial extent of disturbances in spruce-fir forests strongly determines the pathway in early succession. Contrary to earlier descriptions of clearly distinguishable optima phases, our data did not reveal a relationship between stand structure and species composition for the early, mid-, and late optimum phases. Although the reserves investigated here are characterized by highly different climatic and soil conditions, their temporal development was found to fit well into a single successional scheme, suggesting that in spruce-fir mountain forests, the life-history strategies of the tree species may have a stronger influence on successional trajectories than site conditions per se. [ABSTRACT FROM AUTHOR]

It is well known that vegetation dynamics at the catchment scale depends on the prevailing weather and soil moisture conditions. Soil moisture, however, is not equally distributed in space due to differences in topography, weather patterns, soil properties and the type and amount of vegetation cover. To elucidate the complex interaction between vegetation and soil moisture, the dynamic vegetation model LPJ-GUESS (), which provides estimations of vegetation dynamics, but does not consider lateral water fluxes was coupled with the hydrological TOPMODEL (cf. ) in order to be able to evaluate the importance of these lateral fluxes. The new model LG-TM was calibrated and validated in two climatically different mountain catchments. The estimations of runoff were good, when monthly and weekly time scales were considered, although the low flow periods at winter time were somewhat underestimated. The uncertainty in the climate induced change vegetation carbon storage caused by the uncertainty in soil parameters was up to 3–5kgCm−2 (depending on elevation and catchment), compared to the total change in vegetation carbon storage of 5–9kgCm−2. Therefore accurate estimates of the parameters influencing the water holding capacity of the soil, for example depth and porosity, are necessary when estimating future changes in vegetation carbon storage. Similarly, changes in plant transpiration due to climatic changes could be almost double as high (88mmm−2) in the not calibrated model compared to the new model version (ca 50mmm−2 transpiration change). The uncertainties in these soil properties were found to be more important than the lateral water exchange between grid cells, even in steep topography at least for the temporal and spatial resolution used here. [Copyright &y& Elsevier]

Background insect herbivory, in addition to insect outbreaks, can have an important long term influence on the performance of tree species. Since a projected warmer climate may favour insect herbivores, we use a dynamic ecosystem model to investigate the impacts of background herbivory on vegetation growth and productivity, as well as distribution and associated changes in terrestrial ecosystems of northern Europe. We used the GUESS ecosystem modelling framework and a simple linear model for including the leaf area loss of Betula pubescens in relation to mean July temperature. We tested the sensitivity of the responses of the simulated ecosystems to different, but realistic, degrees of insect damage. Predicted temperature increases are likely to enhance the potential insect impacts on vegetation. The impacts are strongest in the eastern areas, where potential insect damage to B. pubescens can increase by 4-5%. The increase in insect damage to B. pubescens results in a reduction of total birch leaf area (LAI), total birch biomass and birch productivity (Net Primary Production). This effect is stronger than the insect damage to leaf area alone would suggest, due to its second order effect on the competition between tree species. The model's demonstration that background herbivory may cause changes in vegetation structure suggests that insect damage, generally neglected by vegetation models, can change predictions of future forest composition. Carbon fluxes and albedo are only slightly influenced by background insect herbivory, indicating that background insect damage is of minor importance for estimating the feedback of terrestrial ecosystems to climate change. [ABSTRACT FROM AUTHOR]

The dynamic vegetation model (LPJ-GUESS) is used to project transient impacts of changes in climate on vegetation of the Barents Region. We incorporate additional plant functional types, i.e. shrubs and defined different types of open ground vegetation, to improve the representation of arctic vegetation in the global model. We use future climate projections as well as control climate data for 1981-2000 from a regional climate model (REMO) that assumes a development of atmospheric CO2-concentration according to the B2-SRES scenario [IPCC, Climate Change 2001: The scientific basis. Contribution working group I to the Third assessment report of the IPCC. Cambridge University Press, Cambridge (2001)]. The model showed a generally good fit with observed data, both qualitatively when model outputs were compared to vegetation maps and quantitatively when compared with observations of biomass, NPP and LAI. The main discrepancy between the model output and observed vegetation is the overestimation of forest abundance for the northern parts of the Kola Peninsula that cannot be explained by climatic factors alone. Over the next hundred years, the model predicted an increase in boreal needle leaved evergreen forest, as extensions northwards and upwards in mountain areas, and as an increase in biomass, NPP and LAI. The model also projected that shadeintolerant broadleaved summergreen trees will be found further north and higher up in the mountain areas. Surprisingly, shrublands will decrease in extent as they are replaced by forest at their southern margins and restricted to areas high up in the mountains and to areas in northern Russia. Open ground vegetation will largely disappear in the Scandinavian mountains. Also counter-intuitively, tundra will increase in abundance due to the occupation of previously unvegetated areas in the northern part of the Barents Region. Spring greening will occur earlier and LAI will increase. Consequently, albedo will decrease both in summer and winter time, particularly in the Scandinavian mountains (by up to 18%). Although this positive feedback to climate could be offset to some extent by increased CO2 drawdown from vegetation, increasing soil respiration results in NEE close to zero, so we cannot conclude to what extent or whether the Barents Region will become a source or a sink of CO2. [ABSTRACT FROM AUTHOR]

We tested the sensitivity of a dynamic ecosystem model (LPJ-GUESS) to the representation of soil moisture and soil temperature and to uncertainties in the prediction of precipitation and air temperature. We linked the ecosystem model with an advanced hydrological model (JULES) and used its soil moisture and soil temperature as input into the ecosystem model. We analysed these sensitivities along a latitudinal gradient in northern Russia. Differences in soil temperature and soil moisture had only little influence on the vegetation carbon fluxes, whereas the soil carbon fluxes were very sensitive to the JULES soil estimations. The sensitivity changed with latitude, showing stronger influence in the more northern grid cell. The sensitivity of modelled responses of both soil carbon fluxes and vegetation carbon fluxes to uncertainties in soil temperature were high, as both soil and vegetation carbon fluxes were strongly impacted. In contrast, uncertainties in the estimation of the amount of precipitation had little influence on the soil or vegetation carbon fluxes. The high sensitivity of soil respiration to soil temperature and moisture suggests that we should strive for a better understanding and representation of soil processes in ecosystem models to improve the reliability of predictions of future ecosystem changes. [ABSTRACT FROM AUTHOR]

Forest successional trajectories covering the last 2000 yr from a mixed deciduous forest in Denmark show a gradual shift in dominance fromTilia cordatatoFagus sylvaticaand a recent increase in total forest basal area since direct management ceased in 1948. The successions are reconstructed by combining a fifty-year record of direct tree observations with local pollen diagrams from Draved Forest, Denmark. Five of the seven successions record a heathland phase of Viking Age dating from 830 AD. The anthropogenic influence is considerable throughout the period of study even though Draved contains some of the most pristine forest stands in Denmark. Anthropogenic influence including felling masks the underlying natural dynamics, with the least disturbed sites showing the smallest compositional change. Some effects of former management, such as loss ofTilia cordatadominance, are irreversible. Artificial disturbance, particularly drainage, has accelerated and amplified the shift towardsFagusdominance that would have occurred on a smaller scale and at a slower rate in the absence of human intervention. [ABSTRACT FROM AUTHOR]

Highlights: [•] We model soil hydrology in dynamic vegetation models based on observed soil data. [•] When water is scarce, carbon uptake differs depending on soil assumptions. [•] Hydrology overrides plant water uptake in DVMs. [•] Relative vertical root distribution is more important than rooting depth in DVMs. [Copyright &y& Elsevier]

Aim Despite increasing evidence for plant growth often being limited by sink (meristem) activity rather than source (photosynthesis) activity, all currently available dynamic global vegetation models ( DGVMs) simulate plant growth via source-limited processes. For a given climatic region, this may lead to an overestimation of carbon stock per unit surface area, particularly if a model fails to correctly predict forest cover. Our aim is to improve the Lund- Potsdam- Jena (LPJ) DGVM by replacing the source-limited ( SoL) tree growth algorithm by a sink-limited ( SiL) one. Location Our analysis focuses on the cold tree line at high latitudes and altitudes. We study two altitudinal transects in the Swiss Alps and the northern tree line. Methods We limit annual net primary productivity of the LPJ DGVM by an algorithm based on the annual sum of growing degree-days ( GDD), assuming that maximum plant growth is reached asymptotically with increasing GDD. Results Comparing simulation results with observational data, we show that the locations of both the northern and the alpine tree line are estimated more accurately when using a SiL algorithm than when using the commonly employed SoL algorithm. Also, simulated carbon stocks decrease in a more realistic manner towards the tree line when the SiL algorithm is used. This has far-reaching implications for estimating and projecting present and future carbon stocks in temperature-limited ecosystems. Main conclusions In the range of 60-80° N over Europe and Asia, carbon stored in vegetation is estimated to be c. 50% higher in the LPJ standard version ( LPJ- SoL) compared with LPJ- SiL, resulting in a global difference in estimated biomass of 25 Pg ( c. 5% of the global terrestrial standing biomass). Similarly, the simulated elevation of the upper tree line in the European Alps differs by c. 400 m between the two model versions, thus implying an additional overestimation of carbon stored in mountain forests around the world. [ABSTRACT FROM AUTHOR]

We review observational, experimental, and model results on how plants respond to extreme climatic conditions induced by changing climatic variability. Distinguishing between impacts of changing mean climatic conditions and changing climatic variability on terrestrial ecosystems is generally underrated in current studies. The goals of our review are thus (1) to identify plant processes that are vulnerable to changes in the variability of climatic variables rather than to changes in their mean, and (2) to depict/evaluate available study designs to quantify responses of plants to changing climatic variability. We find that phenology is largely affected by changing mean climate but also that impacts of climatic variability are much less studied, although potentially damaging. We note that plant water relations seem to be very vulnerable to extremes driven by changes in temperature and precipitation and that heatwaves and flooding have stronger impacts on physiological processes than changing mean climate. Moreover, interacting phenological and physiological processes are likely to further complicate plant responses to changing climatic variability. Phenological and physiological processes and their interactions culminate in even more sophisticated responses to changing mean climate and climatic variability at the species and community level. Generally, observational studies are well suited to study plant responses to changing mean climate, but less suitable to gain a mechanistic understanding of plant responses to climatic variability. Experiments seem best suited to simulate extreme events. In models, temporal resolution and model structure are crucial to capture plant responses to changing climatic variability. We highlight that a combination of experimental, observational, and/or modeling studies have the potential to overcome important caveats of the respective individual approaches. [ABSTRACT FROM AUTHOR]

Dynamic vegetation models are important tools in ecological research, but not all processes of vegetation dynamics are captured adequately. Tree mortality is often modeled as a function of growth efficiency and maximum age. However, empirical studies have shown for different species that slow-growing trees may become older than fast-growing trees, implying a correlation of mortality with growth rate and size rather than age. We used the ecosystem model LPJ-GUESS to compare the standard age-dependent mortality with two size-dependent mortality approaches. We found that all mortality approaches, when calibrated, yield a realistic pattern of growing stock and Plant Functional Type (PFT) distribution at five study sites in Switzerland. However, only the size-dependent approaches match a third pattern, i.e. the observed negative relationship between growth rate and longevity. As a consequence, trees are simulated to get older at higher than at lower altitudes/latitudes. In contrast, maximum tree ages do not change along these climatic gradients when the standard age-dependent mortality is used. As tree age and size determine forest structure, our more realistic mortality assumptions improved forest biomass estimation, but indicate a potential decline of carbon storage under climate change. We conclude that tree mortality should be modeled as a function of size rather than age. [Copyright &y& Elsevier]

This paper discusses the effects of vegetation cover and soil parameters on the climate change projections of a regional climate model over the Arctic domain. Different setups of the land surface model of the regional climate model HIRHAM were realized to analyze differences in the atmospheric circulation caused by (1) the incorporation of freezing/thawing of soil moisture, (2) the consideration of top organic soil horizons typical for the Arctic and (3) a vegetation shift due to a changing climate. The largest direct thermal effect in 2 m air temperature was found for the vegetation shift, which ranged between −1.5 K and 3 K. The inclusion of a freeze/thaw scheme for soil moisture shows equally large sensitivities in spring over cool areas with high soil moisture content. Although the sensitivity signal in 2 m air temperature for the experiments differs in amplitude, all experiments show changes in mean sea level pressure (mslp) and geopotential height (z) throughout the troposphere of similar magnitude (mslp: −2 hPa to 1.5 hPa, z: −15 gpm to 5 gpm). This points to the importance of dynamical feedbacks within the atmosphere-land system. Land and soil processes have a distinct remote influence on large scale atmospheric circulation patterns in addition to their direct, regional effects. The assessment of induced uncertainties due to the changed implementations of land surface processes discussed in this study demonstrates the need to take all those processes for future Arctic climate projections into account, and demonstrates a clear need to include similar implementations in regional and global climate models. [ABSTRACT FROM AUTHOR]

The EU project BALANCE (Global Change Vulnerabilities in the Barents region: Linking Arctic Natural Resources, Climate Change and Economies) aims to assess vulnerability to climate change in the Barents Sea Region. As a prerequisite the potential impact of climate change on selected ecosystems of the study area has to be quantified, which is the subject of the present paper. A set of ecosystem models was run to generate baseline and future scenarios for 1990, 2020, 2050 and 2080. The models are based on data from the Regional Climate Model (REMO), driven by a GCM which in turn is forced by the IPCC-B2 scenario. The climate change is documented by means of the Köppen climate classification. Since the multitude of models requires the effect of climate change on individual terrestrial and marine systems to be integrated, the paper concentrates on a standardised visualisation of potential impacts by use of a Geographical Information System for the timeslices 2050 and 2080. The resulting maps show that both terrestrial and marine ecosystems of the Barents region will undergo significant changes until both 2050 and 2080. [ABSTRACT FROM AUTHOR]

Climate change is expected to alter the distribution of habitats and thus the distribution of species connected with these habitats in the terrestrial Barents Sea region. It was hypothesised that wild species connected with the tundra and open-land biome may be particularly at risk as forest area expands. Fourteen species of birds were identified as useful indicators for the biodiversity dependent upon this biome. By bringing together species distribution information with the LPJ-GUESS vegetation model, and with estimates of future wild and domestic reindeer density, potential impacts on these species between the present time and 2080 were assessed. Over this period there was a net loss of open land within the current breeding range of most bird species. Grazing reindeer were modelled as increasing the amount of open land retained for nine of the tundra bird species. [ABSTRACT FROM AUTHOR]

In the context of the EU-Project BALANCE (http://balance-eu.info) the regional climate model REMO was used for extensive calculations of the Barents Sea climate to investigate the vulnerability of this region to climate change. The regional climate model REMO simulated the climate change of the Barents Sea Region between 1961 and 2100 (Control and Climate Change run, CCC-Run). REMO on ~50 km horizontal resolution was driven by the transient ECHAM4/OPYC3 IPCC SRES B2 scenario. The output of the CCC-Run was applied to drive the dynamic vegetation model LPJ-GUESS. The results of the vegetation model were used to repeat the CCC-Run with dynamic vegetation fields. The feedback effect of the modified vegetation on the climate change signal is investigated and discussed with focus on precipitation, temperature and snow cover. The effect of the offline coupled vegetation feedback run is much lower than the greenhouse gas effect. [ABSTRACT FROM AUTHOR]