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Vegetation trends in Portugal point to a generalized greening in this territory in the period 1982-2012, in agreement with global greening patterns. Nonetheless, vegetation dynamics may be altered by natural hazards, such as fires and droughts, and also by human activities like land management and land use change. The identification of trend shifts allows to better understand their impacts on vegetation, as well as the recovery after these disturbances.A recently developed a high-resolution (1.1km) spatial dataset of the Normalized Difference Vegetation Index (NDVI) for Portugal spanning the period from 1981 to 2015 is used in the present work. NDVI was derived from the Advanced Very High Resolution Radiometer (AVHRR) sensor on board of the NOAA satellites. Land cover and land cover change are identified using CORINE Land Cover maps. Trends are assessed on seasonally adjusted NDVI time series. Results show at least one breakpoint in the NDVI time series over the study area. Moreover, the majority of the breakpoints separate segments of increasing trend, indicating the recovery of the vegetation after the disturbance. In particular, the extreme drought event of 2005 is pointed out as one main cause of the vegetation shifts occurring, namely in central and southern Portugal, highlighting that water availability plays a major role in vegetation activity in these areas. Additionally, the 2005 fire season presents the second highest value of burned area during the study period, and it is also responsible for a significant number of vegetation shifts. Vegetation behaviour and recovery over the areas affected by drought and/or fires are analysed. Land cover change is also a likely driver of vegetation shifts, since they are both identified on a pixel level on some regions.Acknowledgements: This work was partially supported by national funds through FCT (Fundação para a Ciência e Tecnologia, Portugal) under Project IMDROFLOOD WaterJPI/0004/2014) and the research grant attributed to Ana Russo (SFRH/BPD/99757/2014). [ABSTRACT FROM AUTHOR]

Large part of Eastern Siberia is covered by permafrost and is accessible only by rivers in summer and ice roads in winter. They critically depend on ice formation dates and thickness. Ground thawing, subsidence, thermokarst and other hazardous cryogenic processes could lead to failure of infrastructure. The study aimed at assessment of current and future climate-induced changes of river ice and active layer depth in Central Yakutia. Hydrological models Hydrograph and HYPE were employed to simulate active layer depth and river ice respectivelywith ensembles of bias-corrected CMIP5 climate model outputs (1971-2100) as forcing representing the emission scenarios RCP4.5 and RCP8.5.Air temperature in Yakutsk has increased from -10.4 °C (1951-1978) to -8.7 °C (1979-2012). It is expected to further increase by 3.5°C and 6.6°C according to RCP4.5 and RCP8.5 by the end of XXI century. The mean ice thickness of the Lena River at Yakutsk in March and April has decreased in March and April during the period 1955-2015 by 20-35%. River breakup is shifting to earlier dates at a rate of 1.2 days per decade (1939-2015). Ground temperature and thawing depth are relatively stable for the period 1982-2012.Hydrograph model was applied in a lumped way to simulate active layer depth. The dominant landscapes in Central Yakutia are larch forest with sandy soil, pine forest with sandy soil, larch forest with loamy soil, alas depressions covered by grassland with loamy soil, inter-alas areas covered by larch and birch forests, and marsh. Model parameters were estimated based on field data that is representative for above-mentioned landscapes. Validated on the historical observations Hydrograph model was used for future projection. According to RCP4.5 practically no changes of active layer depth are expected in alas and interalas areas. Deepening of active layer in marshes, pine and larch forests with sandy soils for period 2071-2100 would reach 47-66 cm comparative to 2011-2040. According to extreme RCP8.5 scenario permafrost would completely thaw in upper 5 m in three landscapes with sandy soils while thawing depth would increase only by 15-27 cm in other three landscapes with loamy soils. Simulation results suggest relatively high resilience of alas, interalas areas and larch forests with loamy soils to future warming.The Arctic-HYPE model was applied to simulate ice depths and freeze-up and break-up dates at river ice road crossings in the Lena, Aldan and Viluy rivers. Local observations from the Lena river at Tabaga, Yakutsk and Khangalassy were used for critical model improvements. Projections towards the end of XXI century under RCP4.5 and RCP8.5 suggests that the ice cover period is likely to be one month shorter than today, both through earlier break-up and later ice formation dates, and reduction of annual maximum ice depth would be in the range 40 to 70 cm. [ABSTRACT FROM AUTHOR]

Today, peatland management is more and more perceived as a fundamentally important land use based greenhouse gas (GHG) mitigation option. Understanding current peatland use and expected changes provides a background to develop recommendations for future management frameworks and can facilitate good peatland management practices (PMP) permitting long-term emission mitigation in Europe. The objective of this study was to exemplify knowledge and stakeholder's views on peatland management status and development in Europe and to show the relationship between PMP with climate mitigation potential under different environmental conditions and institutional settings. Our research questions, to facilitate in-depth examination of PMP were: i) Which PMP exist and what are expected trends? ii) What is the current implementation status of PMP with regards to evaluating their GHG mitigation potential? iii) How are GHG emissions and removals from organic soils currently reported to the UNFCCC and what are the challenges in reporting development? iv) Are there governmental incentive-based policy instruments and innovative voluntary private sector initiatives, aiming at PMP that support climate change mitigation?We carried out a web-based survey in eight peatland-rich European countries (Finland, Sweden, Norway, Denmark, UK, the Netherlands, Germany, Poland). 60 experts, including researchers, stakeholders acting as multipliers for farmers (e.g. farmer's associations, NGOs) and government representatives, provided valuable insights on a regional and national level.In our survey, stakeholders saw agriculture as main driver to peatland use, with increased GHG emissions, biodiversity loss and declined water quality as its main impacts. Majority of the stakeholders expected croplands to be used as grasslands and agricultural areas to be rewetted. However, geographic variability of expected land use changes was apparent. Prevailing PMP (such as drainage methods) were also reported to vary significantly across Europe. Therefore, the development and assessment of PMP and especially the policy instruments guiding them should account for the regional drivers and bottlenecks. Survey results further show that a range of PMP, aiming at GHG emission reduction while maintaining production options, are in testing phases across Europe. Only a few, however, can be considered mitigating climate impacts (i.e. good PMP) to the date. It is therefore required to promote further research on the mitigation potential of currently tested PMP. The lack of data (activity, mapping, and emission) and in some cases poor separation of peatlands from other land use types was also seen as a bottleneck for developing evaluation methods for national greenhouse gas reporting to the Intergovernmental Panel on Climate Change (IPCC). Integrating identified good PMP as part of the IPCC reporting, however, would provide positive feedback and motivation for practical implementation. Only few policies and policy instruments directly aiming at GHG mitigation on peatlands exist. Other policy instruments mentioned, may not set GHG mitigation on peatland as the main goal but might have a spill-over effect. Cross-sectoral institutional interlinkages on multiple governance levels indicate that climate change mitigation is just starting to be mainstreamed.The study is part of the PeatWise (Wise use of drained peatlands in a bio-based economy) – project funded by the FACCE ERAGAS. [ABSTRACT FROM AUTHOR]

Ongoing changes in climate coupled with the effect of increasing anthropogenic pressures in alpine regions makes understanding and monitoring species responses and distribution urgent conservation priorities. At the top of the Northern Andes, tropical alpine ecosystems are known as paramos, highly diverse ecosystems and crucial providers of services for more than 30 million people that depend on them for water. Such ecosystems are very sensitive to climate change and can be rapidly affected by any variation in temperature and precipitation at multiple scales. At the local scale, microclimatic changes might affect plant physiological functions, which at larger scales influences community structure and composition. We explored the applicability of UAV-borne optical and hyperspectral imagery to identify a selected set of 10 common paramo species and track changes in its traits at a combination of microclimate resolution and landscape extent. We took UAV-borne optical and hyperspectral images of the 10-ha study area and collected plant cover data on 5 plots for calibration and another 5 plots for independent validation. Mapping plant communities (e.g. frailejonales, shrubs, grasslands) using both optical and hyperspectral imagery was possible as well as the variation in traits per community and among communities. Three species from the genus Espeletia, endemic to the paramo, could be differentiated from one another using hyperspectral imagery. Hyperspectral data was also useful for the identification of some of the grasses, which are commonly difficult to identify in the field. Optical imagery allowed high observer based-mapping accuracy, while hyperspectral imagery was reliable for mapping using modeling approaches (e.g. Maxent). Our study suggests that UAV-borne optical and hyperspectral imagery have a great potential for species and plant traits mapping in the Paramo, and thus provide a valuable addition to field data to monitor species response to global changes from the plant to the landscape scales. Studies at larger extents and in other paramos would allow exploring the variation in spectral signatures among sites. [ABSTRACT FROM AUTHOR]

Environmental models are common tools to simulate fluxes and states within the terrestrial energy and water cycles. Simulation results serve a wide range of purposes from infrastructure planning to weather forecasting. Regardless of the purpose, it is a common task to accurately estimate parameters within the process formulations used in environmental models for each computational unit (i.e., grid cell). The dimensionality of the parameter space is equal to the number of parameters per grid cell times the number of grid cells in distributed large-domain modelling, such as in weather forecasting. Without proper regularization of the parameter space, it is impossible to efficiently estimate parameters in this case. One regularization approach is to estimate constant parameters across the modelling domain, but this does not make use of high-resolution data that is available today (i.e., soil maps and land cover information). The Multiscale Parameter Regionalization (MPR) is a promising alternative that makes use of exactly these data sets.The multiscale parameter regionalization (MPR) translates local land surface properties into model parameters. It consists of two steps: first, it relates local geophysical data sets (e.g., soil maps) to high-resolution model parameters via transfer functions at the native resolution of the input data sets. Second, it upscales the high-resolution model parameters to the modeling scale (i.e., the scale at which the model has been applied). MPR has been introduced in the mesoscale hydrologic model (mHM, Samaniego et al. 2010, Kumar et al. 2013), but has recently been made available as a stand-alone tool.In this study, we use the stand-alone tool of MPR to apply it to the land-surface model HTESSEL. This model is the land-surface component of the ECMWF seasonal forecasting system. It uses a tiling approach to differentiate between different land cover types (e.g., high-grown vegetation and shrubs) and assumes constant parameters for each type. Soil related parameters are also considered for few soil classes for the entire domain. While this covers a large extent of subgrid variability at coarse resolutions, we find that its effect at high resolutions is reduced. In this study, we apply MPR for soil water parameters (e.g., conductivity and porosity) and vegetation parameters (e.g., stomatal conductance) that were identified as sensitive in Orth et al. (2016). We find that MPR provides more accurate fluxes over Europe across different resolutions than constant parameters in HTESSEL because it considers the subgrid variability of parameters. We also find a reduced difference between fluxes estimated at different resolutions by applying MPR (i.e., improved flux-matching).References:Samaniego L., et al. https://doi.org/10.1029/2008WR007327Kumar, R., et al. https://doi.org/10.1029/2012WR012195Orth R., et al. http://journals.ametsoc.org/doi/abs/10.1175/MWR-D-15-0283.1 [ABSTRACT FROM AUTHOR]

Terrestrial carbon dynamics are very sensitive to variations in precipitation. Water limitation to vegetation productivity has been attributed as the main source of variability of the global carbon sink. Plant water stress is highly dependent on precipitation amount and frequency, both of which are expected to change according to the latest climate change projections. For this reason, being able to robustly simulate the sensitivity of plant productivity to changes in precipitation, is crucial.In this study we present the results of a new model-data intercomparison project. In this project eleven terrestrial biosphere models were evaluated in reproducing water and carbon dynamics at 10 sites worldwide where either rainfall exclusion, irrigation, or both treatments were applied. The sites included the LTER tallgrass Konza Prairie (KS, USA) and shortgrass steppe (CO, USA), two semi-arid sites in Israel (Lahav, Matta) primarily vegetated by annuals and shrubs, a mesic grassland (Stubai Valley, Austria), a mesic heathland (Brandbjerg, Denmark), a broadleaf deciduous temperate forest (Walker Branch, MO, USA), two Mediterranean forests (Puechabon, France; Prades, Spain), and a Mediterranean shrubland (Garraf, Spain).Overall the models were able to robustly reproduce the relation between precipitation amount and productivity between sites (i.e. spatial dependence) but diverged on their estimates within sites (i.e. temporal dependence). Most models were able to correctly simulate the overall size effect of productivity reduction/enhancement due to rainfall exclusion/irrigation but had low skill in reproducing the observed interannual variability of net primary productivity. The largest fraction of the model divergence was attributed to the functional form of the water stress factor which exceeded model disagreement related to changes in phenology and carbon allocation. Finally, uncertainties related to the short duration of most experiments, measurement limitations, and the conversion of harvested biomass (i.e carbon stock) to net primary productivity (i.e. carbon flux) could mask key signals related to long term carbon dynamics, highlighting the need of more long term high quality data and the importance of comparing models across each other. [ABSTRACT FROM AUTHOR]

According to IPCC high elevation areas are highly vulnerable to climate change. Since these ecosystems have a considerable carbon stock, it is crucial to investigate the influence of extreme climate conditions such as drought on net ecosystem CO2 fluxes (NEE), the difference between the two components gross primary production (GPP) and ecosystem respiration (Reco). Grasslands cover 20–30% of Swiss landscapes and have a significant carbon stock of about 11% (of total carbon stock of Switzerland according to Bolliger et al. (2008)). However, relative changes in GPP and Reco can transform an ecosystem from a net carbon sink to a net carbon source to the atmosphere, especially under changing environmental conditions. In this study, we aim to understand the impact of extreme summer drought on NEE and evapotranspiration of a Swiss alpine grassland by comparing the year 2018 to the preceding 3-year period. In addition, we studied the influence of a change in snow cover on winter fluxes as an important indicator of climate change. To perform this study, we used continuous eddy covariance data measured for about 4 years at Crap Alv (Alp Weissenstein, CH-AWS, Swiss Fluxnet) located at 2000 m a.s.l. in the Grisons, eastern Switzerland. The site is grazed in summer for about three months from mid-June to mid-September and thus is extensively managed. We hypothesize that the extreme 2018 summer drought reduced carbon uptake while increasing ecosystem respiration and therefore reduced the capacity of the grassland for net CO2 uptake. Bolliger, J., Hagedorn, F., Leifeld, J., Böhl, J., Zimmermann, S., Soliva, R., Kienast, F., 2008. Effects of land-use change on carbon stocks in Switzerland. Ecosystems 11: 895–907. [ABSTRACT FROM AUTHOR]

Vegetated linear dunes (VLDs) are the most common and dominant dune type in the world's deserts. However, the processes of formation and elongation of VLDs, which are partly or fully vegetated, are not well understood because all contemporary VLDs are stable, located in areas that are under low wind power and active varieties are not available for study. Nevertheless, it is assumed that vegetation cover is the main reason for VLD formation, and several theories have been proposed for their formation.According to our conceptual model, VLDs were formed under conditions that prevailed during the Pleistocene but are not present today. Those ancient conditions are characterized by higher wind power that can reduce, but not completely destroy, vegetation cover, leading to the formation of big nebkhas with lee (shadow) dunes behind each nebkha. The lee dunes connect to the nebkha in front of it, forming one elongated linear vegetated dune. The wind that formed the nebkhas and lee dunes also eroded the swales that run parallel to the lee dunes. Accordingly, VLDs develop by elongation of lee dunes and formation of downwind nebkhas, where shrubs or grasses develop. Such nebkhas will form another lee dune, which elongates and forms its own nebkha, and so on. We apply a numerical tool to simulate the formation and elongation dynamics of a linear dune in presence of vegetation, as well as its destabilization after removal of the vegetation cover. In previous work, we modeled the morphodynamics of barchan, transverse, seif and parabolic dunes, as well as the formation of aeolian dune fields under constant vegetation growth rate. Our simulations reproduce the morphology and dynamic behaviour of aeolian dunes while agreeing with quantitative measurements. However, so far there is no model that produces longitudinal alignment of mobile dunes in the presence of a vegetation cover under unidirectional wind. Here we have found that such longitudinal alignment can be obtained by applying a cyclically varying vegetation growth rate with suitably chosen oscillation time period and amplitude. Under these conditions, straight, elongating vegetated dunes develop, which resemble closely the shape of real VLDs. By removing the vegetation cover from a VLD, the dune surface becomes unstable and a train of transverse bedforms (surface sand-waves) develops on the VLD. The size of these transverse bedforms is consistent with the values expected from theory and with field observations performed on a VLD field in NW Negev by Roskin et al. (2011) [Quatern. Sci. Rev. 30, 3364–3380].Overall, field observations and numerical simulations corroborate our conceptual model for VLD formation and instability, and show that the Earth's large VLD fields currently stabilized by vegetation cover can give place to active, migrating transverse dunes if vegetation cover in these fields is reduced as a consequence of 21st century climate change. [ABSTRACT FROM AUTHOR]

Extreme peatland forest burning episodes in Indonesia, notably the 1997-98, 2002, 2006 and 2015 events, are a major source of global atmospheric greenhouse gases and have adverse effects on human health and ecosystems on local and regional scales. The re-occurrence of such episodes has refocused attention on the 2002 ASEAN Agreement on Transboundary Haze Pollution, signed and ratified by a total of 10 ASEAN states, including Indonesia since 2014. An operational fire early warning system based on seasonal forecasts has been identified by these states as a key requirement of the Agreement to help mitigate the impacts of widespread burning and haze. However, such a system currently does not exist. Moreover, to develop such a system, a sound understanding of how fire activity responds to climate and human-driven changes in the region is needed.Past research demonstrates that extreme burning events in Indonesia are induced by drought conditions associated with El-Niño and/or positive Indian Ocean Dipole conditions that disrupt the normal monsoonal rainfall patterns across the maritime continent. Several studies have reported clear correlations between antecedent fire weather and fire activity at regional scales. However, most present-day fires in Indonesia result from human-driven land use and land cover (LULC) change and practices associated with agricultural and plantation activities at local scales, and as a result relationships between fire weather and fire activity can be expected to vary depending on past LULC change. Consequently, any effort to develop an operational fire danger early warning system for Indonesia must account for both fire weather and LULC. However, the impact of the interaction of the two factors on fire activity has received comparatively little quantitative attention.This study addresses this research gap by statistically analysing relationships between fire occurrence, fire weather and LULC change across Indonesia from 2002 through 2018. The study uses individual MODIS active fire detections aggregated to 0.25o grid as a proxy for fire activity. Fire weather is characterised by the Canadian Forest Fire Danger Rating System (CFFDRS) indices; Fire Weather Index (FWI) and Drought Code (DC), which are calculated using ERA-5 climate reanalysis products at 0.25 degree resolution. LULC changes are obtained from South East Asia and Peatland land cover maps and forest cover loss datasets. Previous work conducted at (sub-)regional scales in Indonesia has used piecewise regression to establish threshold values for DC and FWI, above which a precipitous increase in fire activity occurs. We revisit these analyses at finer resolutions to determine how such thresholds shift for various LULC types.Our results indicate that relationships between CFFDRS indices and fire activity vary in space and depend on land cover type. The piecewise regression analyses suggest different threshold values for FWI and DC for different land cover types examined, including pristine versus degraded peatland forests, large-scale plantations and small-holder agriculture areas. These results reinforce the importance of considering LULC as part of any future fire early warning system in Indonesia based on near-time climate forecasts. [ABSTRACT FROM AUTHOR]

Drylands cover approximately 30% of the global land area, and the extent of water-limited ecosystems is predicted to increase due to climate change. Although other ecosystems account for a higher percentage of the global mean net ecosystem exchange (NEE), modelling studies suggest that inter-annual variability in global NEE is dominated by semi-arid ecosystems. Dryland ecosystems are extremely sensitive to precipitation. Consequently, high spatial and temporal variability in CO2 fluxes is common in these biomes, driven by precipitation distribution. This high spatiotemporal variability, coupled with an under-sampling of biogenic flux measurements in these biomes relative to more mesic ecosystems, contributes to greater uncertainty in knowledge of dryland carbon fluxes.As part of a new project investigating how Dryland Regions control Interannual Variability In Global Carbon flux (DRIVING-C), we are quantifying the variability in carbon fluxes around two existing semiarid EC sites. These sites are US-SEG, a Bouteloua-dominated grassland and US-Ses, a Larrea tridentata shrubland, both of which have been running continuously since 2007. At each site, a cluster of four low-cost eddy covariance systems were deployed in October 2018 around the existing flux tower, one located ca. 7 m from the existing tower to replicate its measurements, while the remaining three low cost systems were placed ca. 80 m away at equal intervals around a circle. Each low-cost system is composed by a Gill sonic anemometer placed at 6m height, a Vaisala closed path gas analyser for CO2 fluxes and a relative humidity sensor for H2O fluxes. To our knowledge, this deployment of eight low-cost EC in the south west of US (New Mexico, Sevilleta National Wildlife Refuge) represents the first attempt at investigating biogenic fluxes in semi-arid ecosystems over this short length scales (ca. 100's of m). This presentation will describe the low cost system, and share preliminary results from the first six months of intercomparisons between the ten EC systems. The low-cost towers are operating with satisfactory reliability, with all sensors returning reasonable and consistent values. Over the 3.5 year project, our comparisons with higher cost conventional towers will allow us to evaluate the ability of these low-cost systems to quantify spatial variability of biogenic fluxes and hence to validate the representativeness of conventional single towers at this observation scale. Should the low-cost EC demonstrate to be a reliable complement for the traditional system, this low cost technology could be deployed more widely to help address the issue of undersampling in dryland biomes. [ABSTRACT FROM AUTHOR]

Current Western Palearctic avifauna is reported in the fossil record since the EarlyPleistocene. Bird species have specific needs concerning the habitat, especially interms of vegetation, and are very sensitive to habitat changes. Hence, changes incomposition of avifaunal assemblages can reflect habitat patchiness and evolution of thelandscape through time (especially vegetation features) in response to past climaticoscillations. We present the systematic and taphonomic analysis of the bird fossil remains from thelate MIS 3 of two cave deposits in North-Eastern Italy. Buso Doppio del Broion Cave(Vicenza) is located in the Berici Hills, at 150 meters above sea level (m.a.s.l.), while RioSecco Cave (Pordenone) is situated in the Eastern Carnic Pre-Alps, at 580 m.a.s.l. The twosites provided more than 50 species, all belonging to the extant Western Palearctic avifauna.The ecological requirements of the bird species recovered, suggest the presence of a mosaicof different habitats in the surroundings of the caves during the late MIS 3, representedby open areas like steppe, grasslands and shrublands; conifer or mixed forests;rocky cliffs and wetlands. Within the sedimentary succession of the Buso DoppioCave, the upward increase of bird taxa typical of open environments hints to theexpansion of open areas (e.g., grassland and steppe) in response to the ensuing climatedeterioration related to the onset of the Last Glacial Maximum (MIS 2). Furthermore,in the Buso Doppio Cave deposits the presence of two boreal species currentlyabsent from the Italian avifauna (i.e., Bubo scandiacus and Surnia ulula), along withLagopus mutus, Lyrurus tetrix, Tetrao urogallus, Pyrrhocorax graculus, Pyrrhocoraxpyrrhocorax and Prunella collaris at low heights, represent clear indication of aclimate colder than the present one. This paleoenvironmental and paleoclimaticframework completely agrees with the vegetational profile given by the pollen records ofthe Fimon lake deposits (less than 5 km away from Buso Doppio Cave) and ofthe Azzano Decimo core, in the Friulian Plain (about 40 km south of Rio SeccoCave). This work also provided the first Italian fossil record of two species, Troglodytestroglodytes and Phoenicurus ochruros, and the second Italian Pleistocene fossil record ofSurnia ulula. The taphonomic analysis of the fossil remains detected the contribution ofnocturnal raptors, carnivores and, to a lesser extent, Paleolithic hunter-gatherers groups, in theaccumulation of the bird remains. [ABSTRACT FROM AUTHOR]

Biogenic Volatile Organic Compounds (BVOCs) are reactive hydrocarbons emitted by living organisms, mainly by vegetation, in numerous physiological processes. BVOCs interact with the atmosphere in various ways, and are important for the regional air quality and climate because they can contribute to tropospheric ozone, prolong the lifetime of methane, and enhance aerosol formation and growth. Production and emission of BVOCs from plant leaves is highly regulated by temperature. As the Arctic region currently experiences drastic increases in air temperatures due to the climate warming, it is important to understand how the arctic plants respond to this warming. Arctic plants do not regulate their leaf temperature as well as temperate or tropical plants do and effectively heat up during sunny days. Our aim was to evaluate whether their BVOC emissions follow accordingly.In this project we assessed the influence of leaf temperature on BVOC emission of four common tundra shrubs, deciduous Salix myrsinites and Betula nana, evergreen Cassiope tetragona and Rhododendron lapponicum, over the course of the 2018 growing season on a mesic subarctic tundra heath in Abisko, Sweden. In addition to sampling of volatile emissions over a range of temperatures, we measured various plant traits, such as photosynthesis, stomatal conductance, chlorophyll fluorescence, leaf surface structures, specific leaf area, branch height from the ground and leaf temperature. Climate data were collected from a nearby weather station. The BVOCs were sampled in adsorbent cartridges from a branch enclosed in a leaf cuvette of LI 6400 XT photosynthesis system (Licor, Lincoln, NE, USA) and analyzed using Gas Chromatography – Mass Spectrometry (GC-MS).Results showed that the investigated plants responded differently to increasing temperatures in terms of their BVOC emissions. For instance, the sesquiterpene emissions from Betula had a maximum at around 31°C, above which they decreased drastically, closely following the temperature response of photosynthesis. Monoterpene emissions, however, continued to increase up to the last measurement temperature of around 40°C. This suggests that the monoterpene emissions from Betula were mainly stored VOCs, while sesquiterpenes were newly synthesized. Salix, which is a strong isoprene emitter, showed an increase in isoprene emission even at the highest measurement temperature (above 38°C). This shows, that leaf temperature strongly regulates isoprene emission and that the emission is likely to continue increasing with climate change in the Arctic. Multiple regression will be used to find more relationships between BVOC emission and the measured plants traits. To conclude, the species investigated and the different BVOC groups showed different responses to temperature, suggesting altered BVOC emissions from the arctic ecosystems under climatic warming. The new knowledge acquired in this project will be used to improve the models for BVOC emission to better account for the responses of the Arctic to global environmental change. [ABSTRACT FROM AUTHOR]

Vegetation foliage clumping significantly alters its radiation environment and therefore affects vegetation growth as well as water and carbon cycles. The clumping index (CI) is useful in ecological and meteorological models because it provides new structural information in addition to the effective LAI retrieved from mono-angle remote sensing and allows accurate separation of sunlit and shaded leaves in the canopy. Global and regional scale CI maps have been generated using different approaches from a diverse set of Earth Observation multi-angle datasets across wide range of scales: Multi-angle Imaging SpectroRadiometer (MISR) data at 275 m resolution, the Bidirectional Reflectance Distribution Function (BRDF) product from Moderate Resolution Imaging Spectroradiometer (MODIS) at 500 m resolution, POLarization and Directionality of the Earth's Reflectances (POLDER) data at ~6 km resolution, and most recently from Deep Space Climate Observatory Earth Polychromatic Imaging Camera (DSCOVR EPIC) at 10 km resolution. In this presentation, we characterize and intercompare five available CI products over 20+ forest ecosystem sites, organized within the European Integrated Carbon Observation System (ICOS) research infrastructure, representing diverse forests with different canopy structures. The intercomparison procedure was defined to comply with the best practices proposed by CEOS (Committee on Earth Observation Satellites) Land Product Validation (LPV) sub-group. It corresponds to Stage 1 validation as defined by the CEOS. We illustrate that the vertical distribution of foliage and especially the effect of understory needs to be taken into account while validating foliage clumping products from Earth Observation data with values measured in the field. Satellite measurements respond to the structural effects near the top of canopies, while ground measurements may be biased by the lower vegetation layers. Additionally, caution should be taken regarding the misclassification in land cover maps as their errors can be propagated into the foliage clumping maps. Our results indicate that select datasets can provide good quality clumping index estimates at pertinent scales for modeling local carbon and energy fluxes. [ABSTRACT FROM AUTHOR]

Seasonal snow has received much attention in the community because of its sensitivity to global climate change and obvious effect on regional energy and water balance. Most previous studies focus on the change of seasonal snow variables under global warming, but less work on its inner principle. In this study, we analyzed the variability of snow cover fraction (SCF) and snow depth (SD) over three typical land cover types of open shrubland, evergreen needleleaf and mixed forest, which have widely distribution in Northern Hemisphere (NH). The results demonstrated that there is different annual variation between SCF and SD over all selected regions, which results that the curves of relationship between monthly SCF and SD are not overlapping between the stages of accumulation and ablation. Meanwhile, SCF and SD showed different characters over selected regions, leading to the curves of relationship between SCF and SD taking different shapes in these regions. Such relationship is an effective tool in the simulation of snow processes in model. However, the relationship is not fully considered in the CMIP5, which always has an underestimate in accumulation stage and an overestimate in ablation stage. Therefore, the different relationship between SCF and SD of snow parameterization scheme in the model over regions is a potential improvement topic to the ability of simulation in the future. [ABSTRACT FROM AUTHOR]

Ecosystem services (ES) play an important role in sustaining ecological security, sustainable development and human well-being. Located in the north of Beijing city, the Xilin Gol grassland of Inner Mongolia is vital importance in safeguarding ecological safety and sustainable development of Beijing and the neighboring areas. This study investigated spatio-temporal changes of four critical ES in the Xilin Gol grassland from 1990 to 2016, including net primary productivity (NPP), water yield (WY),soil conservation (SC) and soil loss due to wind (SL), by incorporating multiple data and four widely used biophysical models (CASA, InVEST, USLE and RWEQ). Additionally, the constraint relationship between paired ES was determined by extracting the upper constraint lines from the two-dimensional scatter plots. Research findings indicated that during 1990-2016, NPP fluctuated between years. The amount of WY and SC decreased significantly in 1990-2001(the year of 2001 is the time node for the implementation of ecological restoration project), but slightly enhanced in 2001-2016. SL increased significantly in 1990-2001, but showed a significant downward trend in 2001-2016. Spatially, four ES exhibited significantly spatial heterogeneity. From 2001 to 2016,vegetation restoration(mainly in conjunction with ecological restoration programs),increasing rainfall and the reduction in wind speed produced positive effects on NPP, WY, SC enhancement and SL reduction. With respect to ES constraint line analysis, there was a hump-shaped constraint effect between NPP and SC. In general, the higher NPP amount, the better vegetation growth. Vegetation could effectively inhibit water erosion. As water was the main limiting factor for vegetation growth in the Xilin Gol grassland. Accompanied by the increase of rainfall, NPP also enhanced. When NPP amount exceeded a certain threshold, higher NPP meant more local precipitation, which increased the possibility of water erosion. The gradually increasing constraint effect of higher NPP on WY indicated that, in Xilin Gol grassland, improving NPP might decrease WY. The constraint line method was used to explore the relationships of ES, which could enrich our understanding of interaction between ES and potential influence factors. [ABSTRACT FROM AUTHOR]

Extreme meteorological events are important causes of damages even in the Alpine environment where topography can interfere with windstorms. These events can be characterized by winds up to 190 km/h that can damage human infrastructures and alter intensively the vegetation. Such an event occurred in the night between 28 and 29 October 2019, the low pressure area "Vaia" over Germany caused violent gusts over the eastern Alps, which crashed about 8 million cubic meters of timber. The protective forest, that plays an important role in avalanche and landslide prevention and protection, was uprooted in several areas of the Dolomites (Livinallongo del Col di Lana, Rocca Pietore, Colle Santa Lucia, Alleghe). The occurrence of similar episodes are rare considering that in 1990 the windstorm "Vivian" destroyed the protective forest of Curaglia in the Graubünden Canton (Suisse). The impact of such an event was not limited only to the forest, the "Vaia" windstorm was combined also to an intense alluvial event, similar to that of 1966, that interrupted telecommunications and main and secondary communication routes.This study presents the support provided by the ESA's Sentinel imagery to the identification and mapping of these avalanche risk areas. The Sentinel 2A MSI imagery, 10m of resolutions, collected October 21st (pre-event) and November 10th (post-event), atmospheric corrected, were properly processed to compute NDVI. The multitemporal comparison of the NDVI values, together with the analysis of the spectral values identifying the different land cover classes, allowed the analysis of the forest cover in terms of variation and the discrimination between areas covered by "existing forest" and "uprooted forest". The area under investigation (with an altitude ranging between 1000 and 1900 m a.s.l. and an extension of about 300 km2), is characterized by a vegetation cover where firs and larches are dominant. The analysis considered in addition to the event effects also the seasonal phenological variations of the vegetation according to the forest types present in the study area. The woodland areas with uprooted trees and the deciduous forest without leaves are, in fact, extremely similar from the spectral point of view during this season. The results of the analysis of the images, integrated with the data of the digital elevation model allowed the identification of the areas with the forest on the ground and with a slope greater than 30°. These areas represent the loss of protective forest areas where the attention of decision makers must be focused on. This study can represent a tool for improving the knowledge about extreme events in alpine environments. Furthermore, this study evidences the support of remotely sensed images for a synoptic description of the territory useful for the definition of the avalanche risk. [ABSTRACT FROM AUTHOR]

Application of Machine Learning Technique for Groundwater Potential MappingChangwook Lee (1), Prima Riza Kadavi (1), Sung Jae Park (1), and Mutiara Syifa (1)(1) Division of Science Education, Kangwon National University, 1 Kangwondaehak-gil, Chuncheon-si, Gangwon-do, 24341, South Korea.For sustainable use of groundwater, this study were analyze the potential productivity of groundwater using a machine learning approach and geographic information systems (GIS) in 8 cities in Korea. This model is based on the relationship between groundwater productivity data, including special capacity (SPC) and transmissivity (T) with 16 related conditioning factors including topography factors, hydrology factors, forest factors, land cover factors, soil factors, and geology factors. Machine learning methods from the Weka tool are applied to construct groundwater productivity potential (GPP) maps using the BayesNet and Naive Bayes algorithms that are fast, unbiased, and efficient. The GPP maps were constructed using 70% from total groundwater data. The generated GPP maps are validated using area-under-the-curve (AUC) analysis with well data that has not been used to train the model (30% from total groundwater data). Based on the AUC value of 8 research fields, it can be concluded that the BayesNet model using SPC data is the best model in the study with an average AUC value of 84.2%, followed by the BayesNet model using T data with an average AUC value of 83.9%, the Naïve Bayes model uses SPC data with an average AUC value of 83.64%, and the Naïve Bayes model uses T data with an average value of AUC 83.58%. These results indicate that machine learning methods can be useful for the development of groundwater resources. [ABSTRACT FROM AUTHOR]

Human activities exert an unprecedented reach on the biosphere, a reach that is strengthening in many respects due to climate change. There is a growing body of evidence highlighting that human activities have a direct impact on the global silica cycle. In addition to river damming and nutrient over-enrichment, land cover change is another important way by which humans are altering silica exports from terrestrial to aquatic systems. Understanding the controls on silica exports from terrestrial systems has direct implications for silica availability and carbon cycling in coastal receiving waters, due to the reliance of diatoms on silica. Due to rapid climatic warming, the Arctic is undergoing land cover change in the form of shrub expansion, increasing extent and frequency of wildfires, extended growing season length, and northern migration of the treeline. Moreover, permafrost thaw alters watershed hydrology by deepening flowpath lengths and soil-water interaction times. All of these changes are likely to alter rates of silica exchange between terrestrial and aquatic ecosystems. This talk will synthesize recent findings from the Alaskan Arctic demonstrating how rapid climate warming and associated shifts in watershed land cover and hydrology is altering silica cycling in terrestrial and freshwater aquatic systems. We will present evidence demonstrating that shrub expansion and wildfire both serve to increase the amount of silica sequestered in land plants, strengthening the magnitude of the terrestrial silica pump at local scales. Conversely, degradation of permafrost results and deepening of the active layer increases total silica exports from terrestrial systems via rivers at larger regional scales. It remains to be seen whether small-scale increases in silica retention via land plants can offset larger-scale silica releases from thawing permafrost over time. I will also address the implications of these results in the context of the global silica cycle. [ABSTRACT FROM AUTHOR]

The WUDAPT (World Urban Database and Access Portal Tool) project is an international community-generated urban canopy information and modeling infrastructure to facilitate urban-focused climate, weather, air quality, and energy-use modeling application studies. The goals of WUDAPT are 1) to acquire and make accessible coherent and consistent descriptions and information on form and function of urban morphology relevant to climate, weather, and environment studies on a worldwide basis and 2) to provide a portal with tools that extract relevant urban parameters and properties for models and for model applications at appropriate scales for various applications. Its guiding principle is to generate "fit for purpose" urban data using a globally consistent methodology, based on publicly accessible input data and tools. WUDAPT information is organized by level of detail (L), and data at each level are gathered using distinct methodologies and techniques. The lowest level of detail (L0) maps cities and their surrounding natural landscape into local climate zone (LCZ) types. L1 data use the LCZ maps to provide a sampling context for acquiring and managing information at finer scales. L2 data are complete information on all urban elements (e.g., building footprints, envelope fabrics, and heights).Recently great progress has been made on L0 data. Large-scale continental LCZ mapping is achieved using the state-of-the-art cloud computing resources from Google's Earth Engine, the concept of transferability, sufficient training data and data from several satellite sensors. The accuracy of the resulting large-scale LCZ maps is very good (accuracies > 80% for both urban and natural LCZ), and agreement with meta-information such as ESA CCI land cover, EU's Urban Atlas building height database, and spherical surface fractions (e.g. sky view factor, imperviousness, tree coverage) from Google Street View images is high. Level 1 and 2 is currently testing and implementing an innovative prototype tool called the Digital Synthetic City (DSC) based on inverse procedural modeling. This framework can infer and provide digitally rendered buildings and other urban morphological features from satellite imagery with a high degree of accuracy. The top-down approach will provide the basis and means for generating user specified gridded Urban Canopy Parameters (UCPs) representing the spatial envelope of geometric form and patterns of building and other urban morphological structures for urban modeling applications. Urban experts around the world are being engaged in specialized testbed protocols to test and customize the DSC towards ascertaining and ensuring the accuracy and cultural differences and building typologies are captured using this methodology. Bottoms-up methodologies to generate information on materials and functional aspects of buildings based on building typology and use of crowdsourcing approaches are currently under development. WUDAPT is a successful grassroots effort, and continued community involvement is key to assuring success. Please consider engaging in and/or following the progress online (www.wudapt.org). [ABSTRACT FROM AUTHOR]

Droughts and heat waves deeply interact with the exchange of energy and matterbetween land surface and atmosphere. The conditions associated with a combinedheat wave and drought can have positive or negative effects on the sensible heatflux (H), latent heat flux (LE), and net flux of CO2 (NEE). In return, while eachof these fluxes can exert different local feedbacks on temperature, atmospherichumidity and soil moisture, all of them result in bulk heating of the troposphere (Hand LE through direct local and indirect non-local heat transfer, and NEE throughradiative forcing). H is positively affected by increased solar irradiation, but can besupressed by advection of warm air diminishing the gradient between surface and airtemperature. Potential LE is positively affected by irradiation, temperature and watervapour pressure deficit, but actual LE can be suppressed by stomatal closure ofplants and by reduced soil moisture from low rainfall and high past LE. NEE is theresult of plant photosynthesis (GPP) and plant and soil respiration (R), both ofwhich can be enhanced by high temperatures or irradiation, and suppressed bydrought. Focusing on direct measurements mostly by a network of Eddy-Covariance (EC) stationsof the ICOS (www.icos-ri.eu), TERENO (www.tereno.net) and other networks, wehypothesize that the net effect of the 2018 event at a site, and thus its feedback on globalwarming, depends on the balance between co-existing positive and negative effects of thecombined heat wave and drought on the respective fluxes. Variables such as albedo, growingdegree days (GDD), soil moisture and ecosystem-level water use efficiency help to separatethese co-existing positive and negative effects from each other. Preliminary results indicatedifferent degrees of heterogeneity between sites for different variables. As expected, reducedprecipitation and soil moisture, as well as increased GDD, could be found at almost all sitesin the affected region. NEE was mostly less negative, indicating a weaker sink or evena source for CO2, as expected from past studies on earlier events. The networkdensity and number of site-years available now confirms that this was true for allmajor ecosystem types - forest, grassland and (rainfed) cropland, and resulted inincreased atmospheric CO2 concentrations. However, notable exceptions occurred atelevated low mountain range sites and during early stages of the event, supporting thehypothesis of a balance between positive and negative effects, where the former mayprevail at strongly energy-limited sites with a usually large water surplus. H wasmostly above-average, indicating that local heat production contributed to the eventand was typically not suppressed by warm air advection. LE as well as inferredGPP and R reacted most heterogeneously across sites, demonstrating the largediscrepancy between potentially high fluxes due to high irradiation and temperatureon the one hand, and suppression by water shortage on the other hand. Despitethe variability in LE, its relation to NEE was such that ecosystem-level water usewas less efficient than usual at the majority of sites through reduced CO2 uptake. [ABSTRACT FROM AUTHOR]

High temperatures, low relative humidity, and reductions in soil moisture available to plants under intense drought conditions leads to reductions in photosynthetic activity in many plant functional types. During the summer of 2018, we see this across central and northwestern Europe in our sun-induced fluorescence (SIF) remote sensing product SIFTER [1], suggesting that the terrestrial biosphere took up less carbon from the atmosphere that year than it does under typical summer conditions. We use a variety of atmospheric drivers to generate multiyear soil moisture fields using the 5x5 km hydrological model PCR-GLOBWB, which is subsequently used along with SIF in the biosphere model SiB4 to drive simulations of gross primary production (GPP), following the method of van Schaik et al. 2018 [2]. We optimise the biosphere fluxes first using reported crop yields after Combe et al. 2017 [3] and secondly with observed atmospheric CO₂ mole fractions in the atmospheric inverse system CarbonTracker Europe [4]. We will quantify the impact of the drought on the carbon fluxes of Europe's biosphere using these optimised values, and illustrate the dominant pathways across forests, grasslands, and croplands. The severity, spatial extent, and onset- and recovery-timing of the anomaly in GPP will be compared to other recent notable drought events in EurAsia, such as that of 2003 and 2010. [1] Koren, Gerbrand, et al. "Widespread reduction in sun-induced fluorescence from the Amazon during the 2015/2016 El Niño." Philosophical Transactions of the Royal Society B: Biological Sciences 373.1760 (2018): 20170408.[2] van Schaik, Erik, et al. "Changes in surface hydrology, soil moisture and gross primary production in the Amazon during the 2015/2016 El Nino." Philosophical Transactions of the Royal Society B: Biological Sciences 373.1760 (2018): 20180084.[3] Combe, Marie, et al. "Grain yield observations constrain cropland CO2 fluxes over Europe." Journal of Geophysical Research: Biogeosciences 122.12 (2017): 3238-3259.[4] der Laan-Luijkx, Van, et al. "The CarbonTracker Data Assimilation Shell (CTDAS) v1. 0: implementation and global carbon balance 2001-2015." Geoscientific Model Development10.7 (2017): 2785-2800. [ABSTRACT FROM AUTHOR]

African wetlands in arid and semi-arid regions provide a multitude of ecosystem services andhave been described as the "heart of Sahelian life systems". The Khor Abu Habil alluvialwetlands (Khor is the name given to ephemeral rivers in Sudan) are situated in thesemi-arid zone in the southern part of the Sudan. These ephemeral wetlands are fedby seasonal wadi streams and remain for several months. They provide a habitatfor migratory water birds and play a fundamental role in supporting the humanpopulation (agriculture, grazing, fishing, hunting and construction). In this study weanalyse the Land Use and Land Cover (LULC) dynamics related to agriculturalactivities. We choose agriculture as an entry point because it is the main activity and themain LULC changing factor in the study area. A questionnaire and semi-structuredinterviews were conducted in the study area, documenting different agriculturalactivities and land uses. Additionally, remote sensing data and field data on LULC werecollected and analysed with Google Earth Engine, R and GIS software. Differenttypes of agriculture are practised depending on the soil type. The agriculture inthe wadi pathways depends on floods and the agriculture on the wadi banks is arain-fed. Accordingly, two agricultural calendars were created, namely a rain-fedagricultural calendar and a flood-depending one. Additionally maps illustrating the LULCchange over a year were created. The results helped us to understand the annualchanges in the LULC between the classes agriculture, vegetation, grassland, water andbare soil. Indeed, the same piece of land may be a grassland used by pastoralists aswell as an agricultural land used by farmers, depending on the period of the year.This is a challenge for the creation of classical LULC maps. Wadis or Khors areparticular ecosystems that occur in semi-arid regions. In our study area, the economicactivities show a relationship between land uses and different human communities: theagriculturalists and the pastoralists, who live in synergy with the natural cycles of the seasonsand the wadi waters. The agricultural activities and the different LULC classes aredynamic and vary over the year depending on the wadi flood waters. This characteristicdistinguishes the Khor Abu Habil ecosystem from other ecosystems where LULC classesremain stable most of the year. Our research is part of the FAO-supported projectRESSOURCE with the overall goal to localise and study wetlands of internationalimportance in the sub-saharan Africa and declare them as Ramsar protected zones. [ABSTRACT FROM AUTHOR]

The Red Sea evaporates more than 2 m of water per year. The water vapor is transported bybreezes as far as 200-300 km from the shore. Relative humidity in the vicinity of the Red Sea insummer reaches 80%, but precipitation is scarce except the South West coast of the ArabianPeninsula where mountain ridge reaches 3 km height. The coastal mountains in the central partof the Red Sea are 1 km high and do not trigger the orographic precipitation as it happens in thesouthern part of the Red Sea.In this work, we assess the potential effects of afforestation in the central part of the RedSea Arabian coastal plain on precipitation. Calculations are performed using Weather Researchand Forecast model with 3 km grid spacing. It is assumed that ​ 30 million hectares of bare landis converted to wide leaf forest. The simulations are conducted for Summer season of 2013 withboundary conditions derived from ECMWF 9 km operational analysis.Our simulations show that changes in land cover drive the adjustments of the surfaceheat and moisture balances. The perturbations of heat, moisture, and momentum fluxes affectbreezes, the structure of the planetary boundary layer, cloudiness, and eventually theprecipitation. We found that afforestation can substantially increase the accumulatedprecipitation (up to 40-45 mm per month) over the central coastal plain. The sensitivity ofprecipitation to geo-positioning of the forested area, tree density, classification of vegetationtypes (broad-leaved or needles) was analyzed to maximize the effect.Keywords: Afforestation, Forest, Land cover, Red Sea, Arabian Peninsula, Breeze,Precipitation, Rain enhancement, WRF, ECMWF [ABSTRACT FROM AUTHOR]

The twin German satellites TerraSAR-X and TanDEM-X have been collecting SAR data inbistatic configuration since 2010. This is currently the only available bistatic mission, wherethe interferometric image pair is acquired within the same survey avoiding temporaldecorrelation. In September 2016 the global TanDEM-X DEM was completed achieving anunprecedented homogeneity and accuracy at 12 m horizontal spacing. Its relative heightaccuracy is specified with 90% confidence level below 2 m and under 4 m for flat and steepterrain, respectively. It achieves in more than the half of the tiles globally 1 m and 2 m forflat and steep terrain, respectively. The global absolute accuracy with 90% confidencelevel is below 3.5 m. The unedited 90 m spacing version is freely available sinceOctober 2018. It is purely derived from the acquired interferometric SAR data, whichdelivers reliable values on non-water surfaces, and covers almost the completelandmass 99.89%. The generation of an edited version is planned for the end of2019, where opportune water levelling and gap filling are considered. On the otherhand, it is very important to be aware of the intrinsic radar characteristics whenusing the TanDEM-X global DEM: the height of forested and snow covered areascorresponds to the mean measured phase center that returns from the illuminatedvolume. The wave’s capability to penetrate into a volume depends on its density,structure and the radar frequency. The height of the generated DEM is in thesecases under the surface. For forest the height is over the terrain close to the topof the canopy and for ice under the terrain. This aspect is sometimes seen as anobstacle to use DEM derived by SAR, on the other hand we see an opportunity todetect volume as it leads to a certain amount of decorrelation on the data. As otherdecorrelation can be well assessed is possible to estimate the volume decorrelation fromthe coherence. Since the delivered raw data is remarkably good, further analysishave been conducted and the data has been used for mapping other bio-physicalvariables, based on these principles. Classification algorithms on ice, forest, and waterhave been developed, as well as tested and validated. A global forest map has beenderived and is freely accessible for scientists. Planned is also a global water mapand Antarctica ice facies map. Furthermore the satellites are well in shape andresources are available to acquire the globe at least once more and allow for thegeneration of a change DEM. From the lessons learned the acquisition plan hasbeen adapted in order to achieve the best in the less time, considering an editedversion of the DEM as base. Finally, the land cover maps in addition to the editedDEM and change DEM are very promising products for geomorphology purposes. [ABSTRACT FROM AUTHOR]

Increased reliance on forests for energy, income generation and construction constitutes a growing threat to the physical integrity, richness, biological diversity and productivity of woodlands and shrub lands of Dire Dawa administration. Furthermore, cultivation for subsistence agriculture places intense, competing demands on the remaining vegetation of the administration. Global greenhouse gas emissions from forests, either as a result of deforestation or forest degradation, account for nearly 20% of annual global carbon dioxide emissions. In an effort to stem this contribution to CO2 levels, and thereby to complement the Climate Resilient Green Economy (CRGE) strategy of Ethiopia, payment for ecosystems services (PES) initiatives, such as the reduced emissions from deforestation and degradation (REDD) and other mechanism, have considerably elevated the interest in forest carbon monitoring in the country, resulting in an increased demand from national and sub-national forest management programs to quantify GHGs emission and reduction levels from their jurisdiction. This paper presents field inventory results of the existing vegetation resources over the regional administrative council, and an evaluation of GHG emissions and reduction potentials of the business as usual (BAU) as well as alternative forest development and management pathways for the Dire Dawa administrations' forestry sector, over the period of the second Growth and Transformation Plan (GTP) of Ethiopia (2016-2020). Accordingly two sets of reference (BAU) forest land use and management scenarios and six alternative future forest land use and management scenarios (mitigation scenarios) are developed by downscaling changes from macro-scale global environmental change assessments to the regional and sectoral level. The "prescriptions" for the alternative mitigation scenarios considered include, but not limited to, the use vacant socio-ecological niches (homestead & school forestry), preserving existing forests (i.e., avoiding deforestation), rehabilitation of extremely degraded shrub lands, etc. Subsequently an assessment of the resulting differentials in carbon storage, carbon sequestration, and fluxes of carbon dioxide (CO2), owing to potential implementations of the BAU and alternative future forest LU and management scenarios, are evaluated quantitatively from these scenarios using a spreadsheet carbon accounting tool that incorpo-rates properties of forest management activities integrated with the forest LU projections developed. The BAU and alternative forest land use and managements projections are now fully integrated within the administrations' regional Growth and Transformation Plan (GTP) of the forestry sector, serving as bases to analyze potential GHG impacts of forest based land use and management strategies across the region. [ABSTRACT FROM AUTHOR]

In recent years, a big concern has arisen over large-scale climate-induced reductions on forest growth and survival (Allen et al., 2015), and their impact on the water cycle (Mekonnen & Hoekstra, 2011). Specifically, the higher drought frequency under warmer temperatures (known as "hotter-droughts" or "global change-type droughts") has been related to irreversible changes in the ecosystems composition, including massive tree mortality in forests throughout the world. These effects could be exacerbated under dry and semi-arid climates as the Mediterranean, which is already subjected to drought limiting conditions. During the last decades, hotter-droughts have affected several ecosystems in southeast Spain, sometimes combined with extensive wildfires, aggravating the negative impacts on these ecosystems. Here, we analyze four case studies of these impacts:1) Aleppo pine (Pinus halepensis) forests die-off. Extensive pine mortality rates affected large forests of southeast Spain as a consequence of the extreme drought event occurred in 2014. Severe outbreaks of bark beetle accompanied these events. Afterwards, pine hydric status was slowly recovered in some cases. However, in the most intensively damaged pine populations a subsequent die-off occurred during the following years, independently of precipitation regime. Our results indicate a lack of functional recovery related to non-structural carbohydrates pools and the tree weakness and poor growth due to pest outbreaks.2) Combination of drought and wildfires affects recovery capacity in resprouter species. Many Mediterranean species are able to resprout immediately after fire. The combination of both stressors in a short period of time may produce decay processes in widespread species such as kermes oak (Quercus coccifera). Our results show that individuals affected by drought suffered intense die-off processes in terms of leaf withering and shedding, and loss of aboveground biomass. As a consequence, these shrubs will be more vulnerable in the case of a subsequent wildfire, delaying the recovery capacity and consequently affecting ecosystem resilience (Muñoz, 2019). 3) Changes on species composition and implications on ecohydrological processes. In the same line, plant mortality was observed in some shrubland functional groups in semi-arid communities after the extreme drought event of 2014 (Ruiz-Yanetti, 2017). Plant mortality promoted changes in plant cover affecting ecohydrological processes such as interception, net precipitation and the ratio between the green and blue water (Vicente et al., 2018).4) Future scenarios in a global change context. At local scale, specifically in Alicante province (SE Spain), it has been observed a negative trend in precipitations (−9.4 mm/decade) over the last six decades, until 2012, and a significant positive increment of the mean temperature (+0.18 ºC/decade). According to future climate scenarios, changes in the frequency, intensity, size, and temporal distribution of climate extremes are expected to occur in this region, and it will imply different effects on water balance of forests, from deep recharge to changes in phenological processes, as it has been already observed (Moutahir, 2016).With these studies, we pretend to deepen the knowledge of Global Change impacts on Mediterranean dry and semi-arid ecosystems related to ecosystem resilience and to forest ecohydrological dynamics [ABSTRACT FROM AUTHOR]

The area affected by wildfires is experiencing an overall decrease in the European Mediterranean region. However, there is no clear trend associated to the incidence of large fire events, which continue to pose an important threat, the assets-at-risk. For instance, 2015 and 2017 were years with intense fall-winter fire activity tied to an extended dry period after summer. In this sense, improving wildfire season definition or understanding the underlying spatial and temporal patterns of the drivers of wildfires are key factors towards a more efficient and science-based management. In this work we present a conceptual framework to outline homogeneous spatial-temporal regions in terms of the influence of the main drivers of large fire activity: temperature, wind speed, slope, wildland-Urban-Interface and wildland-Agricultural-Interface. To do so, we combine Geographically Weighted Logit Regression (GWLR) models to parameterize the marginal influence of the drivers, with optimized hierarchical clustering to define uniform regions in terms of the underlying driving factors. These regions were subsequently explored regarding their monthly distribution of fire occurrence and the associated fuel models. In particular, we analyzed large fires (>100 ha) in the period 2010-2015 in Spain. A binary GWLR model was fitted using ignition coordinates as presence locations. Absence locations were randomly extracted according to the observed daily distribution of fires in the study period. Each record was assigned to its corresponding date so that weather factors (temperature and wind speed) could be extracted accordingly. Additionally we retrieved site-specific information about the slope and the distance to urban settlements (WUI) and agricultural lands (WAI). The GWLR model allowed measuring the spatial distribution of the significance of the beta coefficients. We obtained a set of p-values for the beta coefficients at each location expressed as t-values. These values were submitted to hierarchical clustering, optimizing the number of clusters according to the silhouette criteria. The resulting clusters were temporally characterized according to the monthly distribution of the fire events within, and also in terms of the fuel model on which the fire ignited.The method was applied to fires in mainland Spain, obtaining a GWLR explaining about 32% of the variance. We obtained a set of three clusters. Two of them covered the Northwest (Atlantic) region while the third extends along the whole Mediterranean coast and most of the hinterlands. The Mediterranean cluster gathers fires occurring mostly during early summer, starting in pastures with presence of scrub, sparse trees or dense shrublands. Fires within this cluster develop under high temperature and windy situations, preferably in areas closer to urban settlements. A second cluster extends over the Northwest end. It gathers most of the large fire activity, displaying two occurrence peaks in late summer and March. Fires are linked to complex terrains and shrubland mosaics. The remaining cluster covers the northern coast. These are pasture fires, related to agricultural fires during winter, favored by complex terrains and wind speed. [ABSTRACT FROM AUTHOR]

Extreme drought events and plant invasion are concurrently threatening water-limitedecosystems. Especially in the Mediterranean Basin, extreme drought events have increased inthe past years with detrimental effects on many ecosystems. Such events rapidly increase thevulnerability of forest ecosystems by decreasing soil water resources, reducingfitness and growth of trees and finally leading to increased mortality rates. Shrubinvasion can further exaggerate these effects and dangerously decrease tree resilience,eventually turning ecosystems into an alternate state of degraded shrublands. However,experimental evidence on the interaction of recurrent extreme drought and plant invasion isstill scarce and inconclusive, as synergistic effects of different stressors are oftenneglected. Thus, we aim to gain a comprehensive knowledge of the underlying mechanisms ofrecurrent extreme droughts, shrub invasion and their cumulative effects in a Mediterraneanecosystem. To this end, an open savannah-type cork oak (Quercus suber) ecosystem invadedby the native shrub Cistus ladanifer was chosen in South-Eastern Portugal. In threeexperimental blocks, a rainout shelter (30 %) was installed in an uninvaded and invadedcork-oak stand, supplemented by corresponding control plots, in December 2017.Measurements of water and carbon fluxes of trees (n = 36), shrubs (n = 18) and the ecosystemin total will allow to unravel species-specific responses and competition effects underrecurrent extreme droughts. We aim to determine the stress tolerance and critical thresholdsof physiological functioning for both species as well as for the entire ecosystem. Hence, thesedata will help to predict the vulnerability of cork oak ecosystems to progressing climatechange and support future management and conservation decisions for these valuableecosystems. The first year of measurements was dominated by a wet and cold spring, which wasfollowed by a drought period from July to the middle of October. Due to the heavy springrainfall, no significant effects could be observed between treatments. However, aspecies-specific behaviour was evident. Pre-dawn leaf water potentials (ΨPD) of C. ladaniferdecreased from -0.57±0.03 MPa to -3.46±0.05 MPa in the drought period. On the otherhand, ΨPD of Q. suber did not fall below -1.48±0.06 MPa in any treatment. In addition,ecosystem transpiration was clearly dominated by shrubs with maximum sap flow rates (8.8± 0.8 m3 m−2 day−1) over three-fold higher than those of trees. These differences clearlypoint towards two distinctly different drought adaptation strategies of the investigated species. [ABSTRACT FROM AUTHOR]

Climate can be perturbed by land cover change through its influence on the exchange of water, energy, and gases between the land surface and atmosphere. However, in the areas of considerable land cover changes, such as the Horn of Africa, estimating the relative contribution of the associated biophysical changes to the climate through their impact on net land surface temperature dynamics requires further study. Here we used an empirical model driven by time series data (2001 – 2013) from meteorological and moderate-resolution satellite observation, and quantified the relative contribution of radiative (albedo) and non-radiative (evapotranspiration and surface roughness) changes to surface temperature dynamics in the region. In our analysis, the impact of background climate variability signal was removed from every pixel. We find that the conversion of forest to cropland generated maximum net warming (1.3 K) compared with other conversion classes (savanna, shrubland, grassland, and cropland). The warming from the reduction of evapotranspiration and surface roughness process were up to 10-times stronger than the cooling effect from albedo increase (–0.12 K). This result indicates that albedo effect weakly counterbalances the warming from the non-radiative processes, and the climatic impacts of land cover changes were mainly driven by the non-radiative processes in the region. [ABSTRACT FROM AUTHOR]

The southern state of Kerala is an important hotspot for India in terms of tourism, physiography, and biodiversity. Kerala received extremely heavy rainfall and subsequent flooding during August 2018, leading to massive loss and damage. In this study, we investigate the role of changing Land Use Land Cover (LULC) in last three decades on this flooding event. We first assessed the LULC changes for the period 1985 through 2018. We found the massive loss in forest cover during this period with the highest loss between 1995 to 2005. Specifically, many of the evergreen forests changed to either mixed forests or cropland. In the period 2005 to 2018, we found that grasslands and shrublands experienced significant reduction.We did an offline coupling of the Weather Research and Forecasting model (WRF) with WRF-Hydro and investigated the impact of LULC changes on this flooding event. For this, we first calibrated WRF-Hydro against observed discharge over some distributed points based on data availability. The calibrated version of WRF-Hydro was then forced with meteorological inputs from WRF and rainfall from TRMM satellite (for August 2018) to investigate the LULC sensitivity. Using various statistical measures we found that the WRF-WRF-Hydro coupled model was able to simulate the discharge reasonably well. For the given meteorological forcing, different LULC conditions (1985, 1995, 2005, 2018) show varying degree of changes in various parameters of flooding, namely, discharge, depth, and inundation. The LULC changes from 1995 to 2005 show largest changes in flooding parameters, due to the massive loss in forest cover during the same period. Comparing 2005 to 1995, the high flow value (estimated by Q10) is found to have increased by more than 10% for many stations, and for few stations, the increase is even more than 30%. Over central Kerala, the largest increase in surface water head (as high as 40% over some grid points) and inundation extent were found between 1995 to 2005. Notably, LULC changes (and hence its impact on flooding) between 2005 to 2018 have not been as drastic as that between 1995 to 2005. [ABSTRACT FROM AUTHOR]

The Iberian Peninsula is affected by different levels of water scarcity due to extensive droughts that frequently occur, creating conflicts between Portugal and Spain, and even between Spanish autonomic regions. As such, the available water resources need to be more efficiently used to fulfil the multiple demand from different uses (urban consumption, agriculture, industries, tourism), meaning that better management tools are required for that purpose.This study aims to quantify water resources availability in the Iberian Peninsula using the physically-based, fully-distributed MOHID-Land model. This model considers four compartments or mediums (atmosphere, porous media, soil surface and river network), computing water dynamics through the different mediums using mass and momentum conservation equations.The model was implemented in the simulation domains with a resolution of 5 km. Data inputs included the digital terrain model from Shuttle Radar Topography Mission of NASA with a resolution of 90 m; the soil map from the European Soil Data Centre (1:1,000,000); the Corine land cover map from 2012 with a resolution of 100 m; the soil hydraulic properties from the HYPRES class pedotransfer functions; the hourly weather data (precipitation, wind velocity, relative air humidity, solar radiation and surface air temperature) from the SAFRAN model with a resolution of 8 km; the reservoir discharge data from governmental and regional agencies.Simulations were run from October 1979 to June 2014, with model warm-up being set from 1979 to 1985, model calibration from 1985 to 2004, and model validation from 2004 to 2014. The calibration and validation process focused on the comparison of simulated flows with those measured in hydrometric stations (81 stations) with no reservoir influence, and those estimated using satellite products.Four statistical parameters (R2, RMSE, PBIAS and NSE) were used to evaluate model performance. Results differed substantially along the domain, with better results being obtained in the northern region of the Iberian Peninsula when compared with the southern region. This highlight the need for better include information related to water transfers between different catchments in the model. Additionally, information related to reservoir management needs to be included to improve the reliability of model predictions in the downstream areas. Nonetheless, considering the coarse scale of simulation domain, model performance was considered to be generally good considering the scale of the application. [ABSTRACT FROM AUTHOR]

West Africa's Sudanian savannas are one of Africa's high-potential "bread baskets", where surplus food (e.g. millet, sorghum, cowpea and livestock) is being produced. These ecosystems currently undergo pronounced land use changes and will likely face shorter rainy seasons with more extreme rainfall and droughts in the future. This could have serious impacts on the vegetation and its carbon dioxide (CO2) exchange with potentially increasing CO2 emissions accelerating climate warming. Understanding how the CO2 fluxes in this area respond to land use changes and environmental fluctuations, in particular rain events, is essential to design sustainable land use strategies. However, this understanding is hampered by a limited data availability. In this study, we monitored net ecosystem exchange (NEE) of CO2, rainfall and other weather and vegetation parameters during four years (2013-2016) at three savanna sites in southern Burkina Faso and northern Ghana. To this end, a monitoring network of three eddy-covariance stations and nine automatic weather stations was established. The three savannas were characterized by different vegetation due to different land use: i) woody and nearly pristine, ii) a mixture of cropland and grassland and iii) grassland under intensive grazing. Other site characteristics such as climate, soil, or topography chosen were as similar as possible. The impact of rain events on CO2 exchange for these three contrasting ecosystems was analyzed for single rain events (short-term) and on a yearly time scale (long-term). We found that the pristine savanna site was a prominent sink of CO2 (-864 to 605 g CO2 m-2 y-1) while the two degraded sites were net CO2 sources (118 to 605 g CO2 m-2 y-1) with a complex relation with annual rainfall amounts. The NEE responses to single rain events revealed that daytime rain systematically decreased the sink strengths at all sites, which might be associated with decreased light availability. At the degraded sites, additional factors increasing CO2 losses were rain duration and dry spell length. The observed patterns of immediate CO2 flux responses to rainfall at differently used savannas indicate strong internal feedbacks between vegetation and land use changes and raise the question whether the CO2 sink potentials might be overestimated with possible implications for global CO2 budgets. Our findings also suggest that carbon sequestration needs to be taken into account when designing sustainable land-use strategies. [ABSTRACT FROM AUTHOR]

Peatland landscapes such as northern fens are fragmented and patchy in terms of their vegetation, land cover and hydrology. Such heterogeneity leads to variation in biogeochemical cycles of e.g. carbon, nitrogen and water among different land cover types and atmosphere. Thus, there is an urgent need to classify vegetation and land cover accurately. There have been contrasting claims on the spatial resolution requirements for mapping the mosaic-like patterns in treeless northern landscapes such as tundra and peatlands. Some have argued that Landsat-scale resolution (ca. 30 m) is sufficient (Bartsch et al. 2016, Treat et al. 2018). However, according to others, a very-high spatial resolution (of the order of <5 m) is needed for constructing realistic maps of tundra and peatland vegetation (Virtanen and Ek 2014, Siewert et al. 2015, Räsänen et al. 2018). Moreover, recent studies suggest that a centimeter-level spatial resolution, obtained only with unmanned aerial vehicles, should be used for an accurate characterization of patchy landscapes (Palace et al. 2018).We present here a case study highlighting the impact of the choice of the spatial and spectral resolution, dataset combination used as source data in classification, and classification technique on the accuracy of land cover classification in a patchy subarctic landscape. This study will also shed light on the importance of accurate land cover characterization in interpreting chamber and eddy covariance carbon dioxide and methane fluxes measurements with footprint modelling, upscaling the carbon balance to the catchment scale and in process‐based biogeochemical modeling.The study area is located in Kaamanen, northern Finland (69.14°N, 27.27°E; 155 m a.s.l.) in a northern boreal vegetation zone and subarctic climate zone. The main research area is dominated by a treeless mesotrophic patterned fen, characterized by a strong pattern of strings with dwarf shrub vegetation, and flarks with sedge and brown moss vegetation. The catchment area includes also upland pine forests, shrub-dominated pine peatland, and some streams and lakes. Measurements of CO2 and CH4 exchange conducted in 2017 and 2018 using eddy covariance and manual chamber methods at representative land cover types will be used in this study.ReferencesBartsch, A.A. et al. 2016. Land Cover Mapping in Northern High Latitude Permafrost Regions with Satellite Data: Achievements and Remaining Challenges. Remote Sensing 8(12)Palace, M. et al. 2018. Determining subarctic peatland vegetation using an unmanned aerial system (UAS). Remote Sensing 10(9)Räsänen, A. et al. 2018. Predicting biomass in Arctic landscapes using very high spatial resolution satellite imagery and field sampling. International Journal of Remote SensingSiewert, M. B. et al. 2015. Comparing carbon storage of Siberian tundra and taiga permafrost ecosystems at very high spatial resolution. Journal of Geophysical Research-Biogeosciences 120(10): 1973-1994Treat, C. C. et al. 2018. Tundra landscape heterogeneity, not interannual variability, controls the decadal regional carbon balance in the Western Russian Arctic. Global Change Biology 24(11): 5188-5204Virtanen, T., and M. Ek. 2014. The fragmented nature of tundra landscape. International Journal of Applied Earth Observation and Geoinformation 27: 4-12 [ABSTRACT FROM AUTHOR]

The arid and semi-arid ecosystems plays an important role in the terrestrial carbon cycle, but the dynamics of the carbon cycle are not clear while climate changes. Based on the TECO-R model for desert steppe, we estimate one of the most sensitive grassland types in arid and semi-arid ecosystems, desert steppe, Inner Mongolia, with its magnitude, distribution and dynamics of different carbon pools from 2000 to 2017, and the relationship between its changes with environmental factors. The results showed that the average carbon density of ecosystem was 2.51 kg C per square meter, of which the soil accounted for 91.8%. The carbon storage was significantly different among different vegetation biomes, the grassland dominated biome was higher than the shrubland biome, which were 2.85 and 2.19 kg C per square meter, respectively. During the period of study, the carbon sequestration with an annual average of 3.09 Tg C per year. Among the environmentally influencing factors of carbon dynamics, precipitation is the most significant control factor, while temperature has an opposite effect on carbon sequestration, especially for soil carbon pools. The temperature of whole region was widely increased, but the average annual precipitation was relatively stable, making the drought a major limiting factor for the increase of carbon sink capacity in the region. However, in the non-growth season, the precipitation and the temperature were increasing at 0.27 mm per year and 0.055 °C per year respectively, the tendency weakens the negative effects of increased temperature and drought in the growing season on carbon sequestration, and is a major natural contributor to the stabilization of carbon sinks in the desert steppe. [ABSTRACT FROM AUTHOR]

In the framework of CORDEX FPS LUCAS multi-model studies are uncertain about the biophysical impact of afforestation in the northern hemisphere mid-latitude summers, and show either a cooling or warming. The magnitude and direction is still uncertain with implications to the surface energy balance and temperature response. In this study, the effect of three different albedo parameterizations in the regional climate model COSMO-CLM (v5.09) is examined performing de-/afforestation experiments at 0.44° horizontal resolution across the EURO-CORDEX domain during 1986-2015. Idealized de- and af-forestation simulations are compared to a simulation with no land cover change. Emphasis is put on the impact of changes in radiation and turbulent fluxes. A clear latitudinal pattern is found, which results partly due to the strong land cover conversion from forest- to grassland in the high latitudes and open land to forest conversion in mid-latitudes. Afforestation warms the climate in winter, and strongest in mid-latitudes. Results are indifferent in summer owing to opposing albedo and evapotranspiration effects of comparable size but different sign. Thus, the net effect is small for summer. Depending on the albedo parameterization in the model, the temperature effect can turn from cooling to warming in mid-latitude summers. The summer warming due to deforestation to grassland is up to 3 °C higher than due to afforestation. The cooling by grass or warming by forest is in magnitude comparable and small in winter. The magnitude of individual biophysical changes together with the specific climate conditions result in the described near-surface temperature changes. Considering albedos of different vegetation types is more important than soil moisture dependent albedos only. This is important information for model development. [ABSTRACT FROM AUTHOR]

Roots play a key role in plant anchorage, absorption and storage of soil resources (water, nutrients, carbohydrates) and biogeochemical cycles in terrestrial ecosystems. Studying the configuration of the root system and its distribution in the underground space is critical to understanding these effects of the root. For nearly two decades, ground penetrating radar (GPR) has been used as a non-destructive geophysical method to describe the spatial distribution of coarse roots under controlled conditions and field conditions. The detection effect of the ground penetrating radar on the root system depends mainly on the frequency of the radar antenna used and the degree of difference in the relative dielectric constant (ε) between the root and the soil. Nevertheless, the relative permittivity of soil varies greatly between summer and winter due to the effects of seasonal frozen soil. Using this seasonal variation, we evaluated the use of GPR with 900 MHz and 400 MHz antennas to nondestructively delineate the spatial distribution of the roots system of the same shrubs both in summer (August) and winter (January of the second year) under field conditions in the Xilingler shrub grassland ecosystem in Inner Mongolia, China. In summer, the relative dielectric constant difference between root and soil is greater due to the high water content of the roots, and more root signals can be obtained. However, as the soil moisture content is also high, the electromagnetic wave decays faster, which limits the detection depth of the radar, and only the shallow root signals were obtained. In winter, because of the existence of shallow frozen soil, the relative dielectric constant of the soil is low, which is conducive to the penetration of electromagnetic wave into the deep soil, so deeper root information can be obtained. However, the water content of roots will decrease due to the influence of low temperature, which resulting in a smaller difference in the relative dielectric constant between roots and soil. Therefore, the recognition effect on the shallow root system is relatively poor compared with results obtained in summer. Combined with the detection results of the two antenna frequencies (900MHz and 400MHz) in summer and winter, wealth and complete information of shrub root system distribution can be obtained. An effective GPR-based root measurement strategy is proposed by making full use of the seasonal changes of soil environment, which can further enhance the application of GPR in plant root research. [ABSTRACT FROM AUTHOR]

Artificial neural networks (ANNs) are common to solve non-linear relationshipsbetween input and output variables as universal approximators. Functional relationscan often be expressed by shallow and quite simple feedforward networks, alsoknown as multi-layer perceptrons (MLPs). This kind of networks was utilised toestimate the turbulent fluxes of momentum and heat in the atmospheric surfacelayer to enhance the modelling of atmosphere and surface interactions. During thetraining and validation procedure about 390,000 data tuples were processed. For eachdata tuple, measurements of temperature and wind speed in two different heightsabove ground and for validation the scales of wind and temperature u∗ and T∗ wererequired. This data originates from hourly multi-year time series from seven differentmeasurement sites covering three various land usage types namely grassland, forest andwetland.Different network set-ups and combinations of input variables were investigated. Allresults were compared to a conventional iterative calculation method following theMonin-Obukhov similarity theory (MOST). Results of best ANNs are comparable to thosecalculated with the classical MOST. These results and the effects of input dataquality, data preprocessing and network architecture will be presented for selectedMLPs. For example, experiments showed that the use of MPLs with only one singlehidden layer is mostly sufficient to describe the variations of the turbulent fluxes. [ABSTRACT FROM AUTHOR]

Agricultural productivity and food security depends on the application of nitrogen (N) fertilizers. Since the use of N fertilizers has increased, it allowed the world population to increase from 3 to well over 7 billion while food and feed production from arable systems increased by 45–70% since 1950. The excessive use of N fertilizers causes harmful effects to the environment, e.g. increased emissions of nitrous oxide (N2O), nitric oxide (NO), ammonia (NH3) to the atmosphere and leaching of nitrate (NO3) into water bodies. Combined with climate change (temperature increase and precipitation change) will further impact agricultural productivity and N losses. Within the "NITROAUSTRIA" project grassland productivity and associated nitrous oxide (N2O) emissions from Austrian grassland soils were simulated using the LandscapeDNDC model. Five different regions and six different soil types covering more than 70% of intensively managed grassland area in each region were simulated. The objectives of this study were to predict productivity from intensively managed grasslands and associated N2O fluxes under present and future climate change conditions. The baseline scenario (2005 to 2014) compares grassland productivity and N2O fluxes for the five different regions. It proved N2O emission strengths to be higher than emissions from adjacent croplands. For future climate change impact assessment the stochastic weather generator LARS-WG was used. LARS-WG projects local time series of observed weather (temperature, precipitation and radiation) with climate change models. For all five regions, climate change scenarios were generated for RCP4.5 and RCP8.5 covering the time periods 2021-2040, 2041-2060 and 2061-2080. The results of the climate change ensemble simulations indicate that increased temperature will increase grassland productivity in the investigated regions. Even under RCP8.5 conditions, all regions will sustain increasing productivity due to prolonged vegetation periods and higher temperatures. Changed precipitation patterns and increased plant nitrogen uptake will further decrease NO3- leaching in grassland soil. Peak N2O emissions are mainly responsible for high annual fluxes and magnitude and frequency of these peaks may increase in the future. The project revealed the importance of the grassland management to be superior to determine the N2O emissions and NO3- leaching in grassland soil rather than the impacts of future climate change. [ABSTRACT FROM AUTHOR]

Understanding the spatial distribution of populations at a finer spatial scale has important value and foundation for many applications such as ecological environment protection, disaster risk assessment and rescue, business decision-making, regional planning. Remote sensing image products such as nighttime lighting and land cover/land use type, have been widely used to disaggregate a large number of population (such as China) with significant differences in distribution to generate a gridded population map of large scales. However, the natural factors such as the topography, the river network and road network were considered less in previous studies. At the same time, geographic big data (such as POIs) can also be high accurately distinguish population distribution. In addition, the remarkable progress in machine learning provides toolkits for demographers. Therefore, Using existing land use products, nighttime lighting, DEM, POIs and census data, we used Random Forest(RF) models to simulate complex nonlinear correlation between population dependent variable and other independent variables. Finally, we disaggregated China's county-level census data into a 1KM × 1KM grid. The gridded population density datasets obtained by this method can be used to analysis spatial-temporal patterns of population density and provide the potential of geospatial big data for mapping other socioeconomic parameters in the future. [ABSTRACT FROM AUTHOR]

The Mediterranean basin is characterized by the coexistence of various aerosol types such us anthropogenic, desert dust, biomass burning (BB) and background marine particles, with relatively high aerosol load affecting the regional radiative budget. This diversity results in complex aerosol properties with high temporal and spatial variability, which is enhanced by the sporadic character of dust transport and wildfire events. The impact of aerosol load on the regional or local radiative budget is intensified during the summer cloud-free period due to the intense solar radiation. During the warm period the Mediterranean experiences the impact of BB emissions when forest and shrubland fires occur due to favorable meteorological conditions. BB aerosols consisting of two major components, black carbon which is the most absorbing aerosol species and organic aerosols that scatters solar radiation, can have a strong impact on the solar radiation budget, altering atmospheric temperature lapse rates and dynamics over a region.In this work an assessment of temporal variability and spatial distribution of biomass burning aerosol optical properties over the broader Mediterranean basin for the period 2002-2016 is conducted. To that end satellite databases are used. At first, wildfire events are identified in terms of ignition date and geographical location based on MODIS (MODerate resolution Imaging Spectroradiometer) collection 006 data. For our analysis wildfires with a burned area of at least 500ha are considered. Then, for each event aerosol optical properties namely spectral AOD, Ångström Exponent (AE), Fine Fraction (FF) and Aerosol Index (AI), that describe the atmospheric load and size of BB aerosols, are assessed. The relevant data are derived from Collection 006 MODIS-Terra database, except for AI which is taken from TOMS (Total Ozone Mapping Spectrometer) and OMI-Aura (Ozone Monitoring Instrument) databases for the periods 2002-2004 and 2005-2016, respectively. The spatial distribution and the inter-annual variability of BB aerosol optical properties are analyzed. The AI values are greater than 2 with maxima attaining 4.3. Ångström Exponent presents a mean value around 1.5 with maxima exceeding 2.5, whereas mean value of FF is about 0.84. AOD (AOD550) can reach values up to 3.3. For selected large wildfire events (mega-fires) the spatial expansion of smoke plume is estimated through forward-trajectories using the HYSPLIT (Hybrid Single Particle Lagrangian Integrated Trajectory Model) model and then BB aerosol properties are calculated over areas affected by the smoke. [ABSTRACT FROM AUTHOR]

Improved understanding of how vegetation regulates land-atmosphere exchanges of water, carbon and energy is essential to understand the role that vegetation plays in the earth's climate system. The goal here is to use spaceborne radar to monitor into the storage of water in the soil-vegetation continuum and its dynamics in response to environmental conditions.This study is motivated by the potential value of the C-band Advanced Scatterometer (ASCAT) series as a climate data record for monitoring terrestrial vegetation and ecosystem dynamics. The ASCAT instruments currently onboard the Metop-A, -B, and –C satellites build on the success of the European Scatterometer (ESCAT) which flew onboard ERS 1/2 from 1990-2011. Plans to launch SCA on Metop-SG in 2022 mean that the combined data record from this series of satellites will extend for at least 40 years. This data record duration is unique in radar remote sensing and provides an opportunity to observe land surface processes from sub-daily to decadal scales. The value of ASCAT for vegetation monitoring stems from its unique ability to monitor the incidence angle dependence of backscatter. Over land, this can be approximated by a 2nd order Taylor polynomial, the slope and curvature of which are dominated by vegetation rather than soil moisture effects [1]. Recently, a Kernel Smoother has been employed in the TU Wien Soil Moisture Retrieval approach to estimate the slope and curvature dynamically and hence to account for inter-annual variations [2]. Our latest research shows that variations in backscatter, slope and curvature together contain information on vegetation phenology and water dynamics over the North American Grasslands [3]. Seasonal variations in slope support its interpretation as a measure of vegetation density while curvature is also clearly influenced by vegetation phenology. Spatially contiguous anomalies were observed in both slope and curvature when prolonged drought eventually impacted vegetation. Here, results will be presented from an analysis of the Dynamic Vegetation Parameters (DVP) over mainland France to improve our understanding of the DVP, both in terms of their determination, and the physical interpretation of the dynamic vegetation parameters and the bio- and geophysical drivers behind the observed dynamics. In particular, results will be presented to illustrate the degree to which the conclusions drawn over grasslands are applicable to a wider range of cover types. [1] Wagner, W., G. Lemoine, M. Borgeaud, and H. Rott, 1999. A study of vegetation cover effects on ERS scatterometer data. IEEE Transactions on Geoscience and Remote Sensing, 37(2), pp.938-948.[2] Hahn, S., C. Reimer, M. Vreugdenhil, T. Melzer, and W. Wagner, 2017. Dynamic characterization of the incidence angle dependence of backscatter using metop ASCAT. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 10(5), pp.2348-2359.[3] Steele-Dunne, S. C., S. Hahn, W. Wagner and M. Vreugdenhil, Investigating vegetation water dynamics and drought using Metop ASCAT over the North American Grasslands, Remote Sensing of Environment, 2019 (Accepted). [ABSTRACT FROM AUTHOR]