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Trees affect the direction and distribution of crucial components of the hydrological cycle, which were mostly described by measurements on the quantity of precipitation, stemflow and throughfall (TF) collected underneath the canopy. However, due to poor accessibility of tree canopies, our knowledge on hydrological processes within canopies is limited. We propose that canopy structure shapes the spatial distribution of incoming rainfall (RF) within the canopy as well as the intra-canopy TF composition. The Leipzig Canopy Crane facility allows to (i) determine water fluxes from above the canopies (RF) and with TF at top, mid and bottom position within the canopy of three tree species – Quercus robur, Fraxinus excelsior, and Tilia cordata, and (ii) to determine the transport of dissolved and particulate organic carbon and nitrogen with TF. In total, 81 TF collectors were set up every month for a two-weeks-period from March to October 2021.We found amplified water fluxes in TF collectors at top and mid canopy positions compared to incoming RF fluxes, while TF volumes at the bottom decreased. Dimensions of change appear related to RF amount and tree species. Moreover, stability plot analysis indicated that spatial “hot spots” of water fluxes within canopies were temporally persistent.Our results raise the question whether the concept of a “double-funneling of trees” introduced by Johnson and Lehmann (2006) needs to be extended to a “triple-funneling” approach involving the intra-canopy preferential flow of water and elements occurring in upper to mid canopy positions. Canopy spots with higher water and matter accumulation will alter the chemical, biological, and hydrological heterogeneity in canopy habitat structures below, with strong implications for canopy-associated microbial communities and epiphytes and ecosystem functions.

Vertical leaf angles and their temporal variation are directly related to multiple ecophysiological and environmental processes and properties. However, there is no efficient method for tracking leaf angles of plant canopies under field conditions.Here, we present AngleCam, a method to estimate leaf angle distributions from horizontal photographs acquired with timelapse cameras and deep learning. The AngleCam is a pattern recognition model based on convolutional neural networks and was trained with leaf angle distributions obtained from visual interpretation of more than 2500 plant photographs across different species and scene conditions.Leaf angle predictions were evaluated over a wide range of species, plant functional types and scene conditions using independent samples from visual interpretation (R2 = 0.84). Moreover, the method was evaluated using leaf angle estimates obtained from terrestrial laser scanning (R2 = 0.75). AngleCam was successfully tested under field-conditions for the long-term monitoring of leaf angles for two broadleaf tree species in a temperate forest. The plausibility of the predicted leaf angle time series was underlined by its close relationship with environmental variables related to transpiration. Moreover, showed that the variation in leaf angles resembles changes in several leaf-water related traits.The evaluations showed that AngleCam is a robust and efficient method to track leaf angles under field conditions. The output of AngleCam is compatible and relevant for with a range of applications, including functional-structural plant modelling, Earth system modelling or radiative transfer modelling of plant canopies. AngleCam may also be used to predict leaf angle distributions from existing data, such as curated in PhenoCam networks or citizen science projects.

The submission contains following files: Branch_variables.xlsx Variables measured during for individual branches we studied. Each branch is characterized by Tree number and Branch number within the respective tree. The measured variables include leaf area (m2), induction treatment we applied (treatment/control), their height above ground (m), VOC emission level (Total area under the peaks of all VOCs we measured with GC-MS), VOC composition (similarity in VOC profiles emitted by the studied branches as measured on the first PCA axis), Leaf toughness (N), content of HHDPs (mg/g), content of total phenolics (mg/g), predation rates (0.00-1.00), herbivore preference (average area of leaf discs eaten (in mm) by Lymantria dispar in food-choice trials), herbivore abundance (number of caterpillars and sawfly larvae sampled from the given branch standardized by its leaf area), herbivore richness (species richness of caterpillars and sawfly larvae sampled from the given branch). VOCs.xlsx VOCs detected in our samples. Values show means ± st.dev. for control (C) and treated beaches (T) on individual trees. The reported values represent total areas under the peaks as measured with GC-MS. Insects.xlsx Leaf-chewing larvae sampled from treated and control branches on the studied trees. In total, we sampled 898 sawfly larvae and caterpillars. Four larvae with incomplete information on the host tree or branch were excluded from all analyses and are not shown in the data. The data on COI sequences used for insect identification including the standard fields for the BARCODE data standard are available on BOLD (www.boldsystems.org, dx.doi.org/10.5883/DS-LAK2019). Each species is characterized by its Order, Family, Species name, and Species code and the table shows the total number of individuals sampled from control (C) and treated (T) branches in the studied trees. &nbsp

Droughts increasingly threaten the world’s forests and their potential to mitigate climate change. In 2018–2019, Central European forests were hit by two consecutive hotter drought years, an unprecedented phenomenon that is likely to occur more frequently with climate change. Here, we examine tree growth and physiological stress responses (increase in carbon isotope composition; Δδ13C) to this consecutive drought based on tree-rings of dominant tree species in a Central European floodplain forest. Tree growth was not reduced for most species in 2018, indicating that water supply in floodplain forests can partly buffer meteorological water deficits. Drought stress responses in 2018 were comparable to former single drought years but the hotter drought in 2018 induced drought legacies in tree growth while former droughts did not. We observed strong decreases in tree growth and increases in Δδ13C across all tree species in 2019, which are likely driven by the cumulative stress both consecutive hotter droughts exerted. Our results show that consecutive hotter droughts pose a novel threat to forests under climate change, even in forest ecosystems with comparably high levels of water supply.

The phyllosphere is a challenging microbial habitat in which microorganisms can flourish on organic carbon released by plant leaves but are also exposed to harsh environmental conditions. Here, we assessed the relative importance of canopy position—top, mid, and bottom at a height between 31 and 20 m—and tree species identity for shaping the phyllosphere microbiome in a floodplain hardwood forest. Leaf material was sampled from three tree species—maple (Acer pseudoplatanus L.), oak (Quercus robur L.), and linden (Tilia cordata MILL.)—at the Leipzig canopy crane facility (Germany). Estimated bacterial species richness (Chao1) and bacterial abundances approximated by quantitative PCR of 16S rRNA genes exhibited clear vertical trends with a strong increase from the top to the mid and bottom position of the canopy. Thirty operational taxonomic units (OTUs) formed the core microbiome, which accounted for 77% of all sequence reads. These core OTUs showed contrasting trends in their vertical distribution within the canopy, pointing to different ecological preferences and tolerance to presumably more extreme conditions at the top position of the canopy. Co-occurrence analysis revealed distinct tree species-specific OTU networks, and 55–57% of the OTUs were unique to each tree species. Overall, the phyllosphere microbiome harbored surprisingly high fractions of Actinobacteria of up to 66%. Our results clearly demonstrate strong effects of the position in the canopy on phyllosphere bacterial communities in a floodplain hardwood forest and—in contrast to other temperate or tropical forests—a strong predominance of Actinobacteria. Electronic supplementary material The online version of this article (10.1007/s00248-020-01565-y) contains supplementary material, which is available to authorized users.

Intensifying climate change is successively increasing the frequency and intensity of extreme climate events such as droughts. In 2018–2019, Central European forests were hit by two consecutive hotter drought years that were unprecedented in their severity at least in the last 250 years. Such hotter droughts, where drought coincides with a heat wave, may have severe detrimental impacts on forest ecosystems as highlighted by reports of widespread tree defoliation and mortality across Central Europe in 2018–2019. Here, we examine the effect of this unprecedented event on tree growth and physiological stress responses (measured as increase in wood carbon isotope composition, Δδ13C) in a Central European floodplain forest ecosystem. We used tree rings of the dominant tree species Quercus robur, Acer pseudoplatanus and Fraxinus excelsior to compare growth responses, Δδ13C and drought legacy effects during the consecutive drought years 2018–2019 with effects observed in former single drought years (2003, 2006, 2015). We found that tree growth was, except for F. excelsior, not reduced in 2018 and that drought responses in 2018 were comparable to responses in former single drought years. This indicates that water availability in floodplain forests can partly buffer drought effects and meteorological water deficits. Nonetheless, the 2018 drought – which was the hottest and driest year since the start of records – induced drought legacies in tree growth while former drought years did not. Consistent with this observation, all tree species showed strong decreases in growth and increases in Δδ13C in the second hotter drought year 2019. The observed stress responses in 2019 were stronger than in any other examined drought year. We posit that the cumulative effect of two consecutive hotter drought years likely caused this unprecedented stress response across all species. Drought responses were consistent for both drought-stress indicators (growth response and Δδ13C), but the timing and magnitude of responses were species-specific: Q. robur exhibited the overall smallest response, followed by A. pseudoplatanus with the strongest response in F. excelsior. We discuss these species-specific differences in light of the species’ stomatal control (inferred from high-resolution sap flow measurements during drought at our site) and species’ resistance to xylem cavitation. Overall, our findings highlight that consecutive hotter droughts constitute a novel threat to forests, even in floodplain forests with comparably high levels of water supply. These results and similar research may contribute towards understanding and forecasting tree species responses to more frequent hotter droughts under intensifying climate change.

Animals, such as termites, have largely been overlooked as global-scale drivers of biogeochemical cycles1,2, despite site-specific findings3,4. Deadwood turnover, an important component of the carbon cycle, is driven by multiple decay agents. Studies have focused on temperate systems5,6, where microbes dominate decay7. Microbial decay is sensitive to temperature, typically doubling per 10°C increase (decay effective Q10 = ~2)8–10. Termites are important decayers in tropical systems3,11–13 and differ from microbes in their population dynamics, dispersal, and substrate discovery14–16, meaning their climate sensitivities also differ. Using a network of 133 sites spanning 6 continents, we report the first global field-based quantification of temperature and precipitation sensitivities for termites and microbes, providing novel understandings of their response to changing climates. Temperature sensitivity of microbial decay was within previous estimates. Termite discovery and consumption were both much more sensitive to temperature (decay effective Q10 = 6.53), leading to striking differences in deadwood turnover in areas with and without termites. Termite impacts were greatest in tropical seasonal forests and savannas and subtropical deserts. With tropicalization17 (i.e., warming shifts to a tropical climate), the termite contribution to global wood decay will increase as more of the earth’s surface becomes accessible to termites. Acknowledgements. For materials, field, and lab assistance, we thank the Australian Landscape Trust Team, Juan Martínez de Aragón, Eric Roy, Hugh Wilson, Kylie Brice, Bethanie Coleman, Brendan Delroy, Coline Deveautour, Suzanne Donn, Generci Assis Neves, Ricardo Marques Barreiros, Ricardo Marques Barreiros, Generci Assis Neves from Resineves Agroflorestal company, Alfred Lochner, Pousada Vale do Céu, Humberto Robles, María M. Rivera, and Grant Kirker. Steve Allison and Tom Crowther provided comments on the manuscript and Abbey Yatsko helped with figure and manuscript formatting. Funding for this work was provided by US National Science Foundation (DEB-1655759, 2149151, 1713502, 1713435, 1647502, 1546686, 1831952), George Washington University, USDA Forest Service, Centre College Faculty Development Funds, Australia Terrestrial Ecosystem Research Network (TERN) National Collaborative Research Infrastructure Strategy (NCRIS), Royal Society-FCDO Africa Capacity Building Initiative, New Phytologist Foundation, Fondecyt grant:1160329, Coordenação de Aperfeiçoamento de Pessoal de Nível Superior, Brasil (CAPES), Department of Ecology and Conservation of the Federal University of Lavras, CNPq, FAPEMIG, Australian Academy of Science 2017 Thomas Davies Research Grant, Australian Research Council (DP160103765), UK National Environment Research Council (NE/L000016/1), Fundação de Amparo à Pesquisa do Estado de São Paulo, Brazil (NERC - FAPESP)19/07773-1, Environment Research and Technology Development Fund (ERTDF; JPMEERF15S11420) of the Environmental Restoration and Conservation Agency (ERCA) of Japan, COLCIENCIAS (No. FP44842-046-2017), Spanish Government (grant PID2019-110521GB-I00), Catalan Government (grant SGR 2017-1005), Fundación Ramón Areces (grant ELEMENTAL-CLIMATE), Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Agencia Nacional de Promoción Científica y Tecnológica (ANPCyT) PICT 2019- 2472, National Agency for the Promotion of Research, Technological Development and Innovation, Scientific and Technological Research Project 2018-01561 (PICT 2018- 01561), iDiv German Research Foundation (DFG– FZT 118, 202548816), European Research Council (ERC), European Union's Horizon 2020 research and innovation program (grant agreement no. 677232).

Societal Impact Statement Pollen relates to many aspects of human and environmental health, which protection and improvement are endorsed by the United Nations Sustainable Development Goals. By highlighting these connections in the frame of current challenges in monitoring and research, we discuss the need of more integrative and multidisciplinary pollen research related to societal needs, improving health of humans and our ecosystems for a sustainable future. Summary Pollen is at once intimately part of the reproductive cycle of seed plants and simultaneously highly relevant for the environment (pollinators, vector for nutrients, or organisms), people (food safety and health), and climate (cloud condensation nuclei and climate reconstruction). We provide an interdisciplinary perspective on the many and connected roles of pollen to foster a better integration of the currently disparate fields of pollen research, which would benefit from the sharing of general knowledge, technical advancements, or data processing solutions. We propose a more interdisciplinary and holistic research approach that encompasses total environmental pollen diversity (ePD) (wind and animal and occasionally water distributed pollen) at multiple levels of diversity (genotypic, phenotypic, physiological, chemical, and functional) across space and time. This interdisciplinary approach holds the potential to contribute to pressing human issues, including addressing United Nations Sustainable Development Goals, fostering social and political awareness of these tiny yet important and fascinating particles.

Plant functional traits can predict community assembly and ecosystem functioning and are thus widely used in global models of vegetation dynamics and land–climate feedbacks. Still, we lack a global understanding of how land and climate affect plant traits. A previous global analysis of six traits observed two main axes of variation: (1) size variation at the organ and plant level and (2) leaf economics balancing leaf persistence against plant growth potential. The orthogonality of these two axes suggests they are differently influenced by environmental drivers. We find that these axes persist in a global dataset of 17 traits across more than 20,000 species. We find a dominant joint effect of climate and soil on trait variation. Additional independent climate effects are also observed across most traits, whereas independent soil effects are almost exclusively observed for economics traits. Variation in size traits correlates well with a latitudinal gradient related to water or energy limitation. In contrast, variation in economics traits is better explained by interactions of climate with soil fertility. These findings have the potential to improve our understanding of biodiversity patterns and our predictions of climate change impacts on biogeochemical cycles., Nature Ecology & Evolution, 6 (1), ISSN:2397-334X

1. Root lignin is a key driver of root decomposition, which in turn is a fundamental component of the terrestrial carbon cycle and increasingly in the focus of ecologists and global climate change research. However, measuring lignin content is labor-intensive and therefore not well-suited to handle the large sample sizes of most ecological studies. To overcome this bottleneck, we explored the applicability of high-throughput near infrared spectroscopy (NIRS) measurements to predict fine root lignin content. 2. We measured fine root lignin content in 73 plots of a field biodiversity experiment containing a pool of 60 grassland species using the Acetylbromid (AcBr) method. To predict lignin content, we established NIRS calibration and prediction models based on partial least square regression (PLSR) resulting in moderate prediction accuracies (RPD = 1.96, R2 = 0.74, RMSE = 3.79). 3. In a second step, we combined PLSR with spectral variable selection. This considerably improved model performance (RPD = 2.67, R2 = 0.86, RMSE = 2.78) and enabled us to identify chemically meaningful wavelength regions for lignin prediction. 4. We identified 38 case studies in a literature survey and quantified median model performance parameters from these studies as a benchmark for our results. Our results show that the combination Acetylbromid extracted lignin and NIR spectroscopy is well suited for the rapid analysis of root lignin contents in herbaceous plant species even if the amount of sample is limited.

Sediment and nutrient retention are essential ecosystem functions that floodplains provide and that improve river water quality. During floods, the floodplain vegetation retains sediment, which settles on plant surfaces and the soil underneath plants. Both sedimentation processes require that flow velocity is reduced, which may be caused by the topographic features and the vegetation structure of the floodplain. However, the relative importance of these two drivers and their key components have rarely been both quantified. In addition to topographic factors, we expect vegetation height and density, mean leaf size and pubescence, as well as species diversity of the floodplain vegetation to increase the floodplain’s capacity for sedimentation. To test this, we measured sediment and nutrients (carbon, nitrogen and phosphorus) both on the vegetation itself and on sediment traps underneath the vegetation after a flood at 24 sites along the River Mulde (Germany). Additionally, we measured biotic and topographic predictor variables. Sedimentation on the vegetation surface was positively driven by plant biomass and the height variation of the vegetation, and decreased with the hydrological distance (total R2=0.56). Sedimentation underneath the vegetation was not driven by any vegetation characteristics but decreased with hydrological distance (total R2=0.42). Carbon, nitrogen and phosphorus content in the sediment on the traps increased with the total amount of sediment (total R2=0.64, 0.62 and 0.84, respectively), while C, N and P on the vegetation additionally increased with hydrological distance (total R2=0.80, 0.79 and 0.92, respectively). This offers the potential to promote sediment and especially nutrient retention via vegetation management, such as adapted mowing. The pronounced signal of the hydrological distance to the river emphasises the importance of a laterally connected floodplain with abandoned meanders and morphological depressions. Our study improves our understanding of the locations where floodplain management has its most significant impact on sediment and nutrient retention to increase water purification processes.

Among the many concerns for biodiversity in the Anthropocene, recent reports of flying insect loss are particularly alarming, given their importance as pollinators and as a food source for many predators. Few insect monitoring programs cover large spatial scales required to provide more generalizable estimates of insect responses to global change drivers.We ask how climate and surrounding habitat affect flying insect biomass and day of peak biomass using data from the first year of a new standardized distributed monitoring network at 84 locations across Germany comprising spatial gradient of land-cover types from protected to urban areas.Flying insect biomass increased linearly with monthly temperature across Germany. However, the effect of temperature on flying insect biomass flipped to negative in the hot months of June and July when local temperatures most exceeded long-term averages.Land-cover explained little variation in insect biomass, but biomass was lowest in forested sites. Grasslands, pastures and orchards harbored the highest insect biomass. The date of peak biomass was primarily driven by surrounding land-cover type, with grasslands especially having earlier insect biomass phenologies.Standardized, large-scale monitoring is pivotal to uncover underlying processes of insect decline and to develop climate-adapted strategies to promote insect diversity. In a temperate climate region, we find that the benefits of temperature on flying insect biomass diminish in a German summer at locations where temperatures most exceeded long-term averages. These results highlighting the importance of local adaptation in climate change-driven impacts on insect communities.

Induction of plant defences can show various levels of localization, which can optimize their efficiency. Locally induced responses may be particularly important in large plants, such as trees, that show high variability in traits and herbivory rates across their canopies. We studied the branch-localized induction of polyphenols, volatiles (VOCs), and changes in leaf protein content in Carpinus betulus L., Quercus robur L., and Tilia cordata L. in a common garden experiment. To induce the trees, we treated ten individuals per species on one branch with methyl jasmonate. Five other individuals per species served as controls. We measured the traits in the treated branches, in control branches on treated trees, and in control trees. Additionally, we ran predation assays and caterpillar food-choice trials to assess the effects of our treatment on other trophic levels. Induced VOCs included mainly mono- and sesquiterpenes. Their production was strongly localized to the treated branches in all three tree species studied. Treated trees showed more predation events than control trees. The polyphenol levels and total protein content showed a limited response to the treatment. Yet, winter moth caterpillars preferred leaves from control branches over leaves from treated branches within C. betulus individuals and leaves from control Q. robur individuals over leaves from treated Q. robur individuals. Our results suggest that there is a significant level of localization in induction of VOCs and probably also in unknown traits with direct effects on herbivores. Such localization allows trees to upregulate defences wherever and whenever they are needed.

1. Among the many concerns for biodiversity in the Anthropocene, recent reports of flying insect loss are particularly alarming, given their importance as pollinators, pest control agents, and as a food source. Few insect monitoring programmes cover the large spatial scales required to provide more generalizable estimates of insect responses to global change drivers. 2. We ask how climate and surrounding habitat affect flying insect biomass using data from the first year of a new monitoring network at 84 locations across Germany comprising a spatial gradient of land cover types from protected to urban and crop areas. 3. Flying insect biomass increased linearly with temperature across Germany. However, the effect of temperature on flying insect biomass flipped to negative in the hot months of June and July when local temperatures most exceeded long-term averages. 4. Land cover explained little variation in insect biomass, but biomass was lowest in forests. Grasslands, pastures, and orchards harboured the highest insect biomass. The date of peak biomass was primarily driven by surrounding land cover, with grasslands especially having earlier insect biomass phenologies. 5. Standardised, large-scale monitoring provides key insights into the underlying processes of insect decline and is pivotal for the development of climate-adapted strategies to promote insect diversity. In a temperate climate region, we find that the positive effects of temperature on flying insect biomass diminish in a German summer at locations where temperatures most exceeded long-term averages. Our results highlight the importance of local adaptation in climate change-driven impacts on insect communities.

Plant functional diversity (FD) is an important component of biodiversity. Evidence shows that FD strongly determines ecosystem functioning and stability and also regulates various ecosystem services that underpin human well-being. Given the importance of FD, it is critical to monitor its variations in an explicit manner across space and time, a highly demanding task that cannot be resolved solely by field data. Today, high hopes are placed on satellite-based observations to complement field plot data. The promise is that multiscale monitoring of plant FD, ecosystem functioning, and their services is now possible at global scales in near real-time. However, non-trivial scale challenges remain to be overcome before plant ecology can capitalize on the latest advances in Earth Observation (EO). Here, we articulate the existing scale challenges in linking field and satellite data and further elaborated in detail how to address these challenges via the latest innovations in optical and radar sensor technologies and image analysis algorithms. Addressing these challenges not only requires novel remote sensing theories and algorithms but also urges more effective communication between remote sensing scientists and field ecologists to foster mutual understanding of the existing challenges. Only through a collaborative approach can we achieve the global plant functional diversity monitoring goal.

Companies lack efficient mechanisms for the systematic and continuous integration of customers in order to generate benefits and to avoid further complicating their internal processes. A gap was recognized that there is a lack of knowledge management competence to anchor customer know-how in business processes on a persistent basis. These initial findings clearly indicate the need for a comprehensive procedural model for continuous customer integration across all stages of the development process and enabling a persistent knowledge representation.

Plant functional diversity (FD) is an important component of biodiversity that characterizes the variability of functional traits within a community, landscape, or even large spatial scales. It can influence ecosystem processes and stability. Hence, it is important to understand how and why FD varies within and between ecosystems, along resources availability gradients and climate gradients, and across vegetation successional stages. Usually, FD is assessed through labor-intensive field measurements, while assessing FD from space may provide a way to monitor global FD changes in a consistent, time and resource efficient way. The potential of operational satellites for inferring FD, however, remains to be demonstrated. Here we studied the relationships between FD and spectral reflectance measurements taken by ESA's Sentinel-2 satellite over 117 field plots located in 6 European countries, with 46 plots having in-situ sampled leaf traits and the other 71 using traits from the TRY database. These field plots represent major European forest types, from boreal forests in Finland to Mediterranean mixed forests in Spain. Based on in-situ data collected in 2013 we computed functional dispersion (FDis), a measure of FD, using foliar and whole-plant traits of known ecological significance. These included five foliar traits: leaf nitrogen concentration (N%), leaf carbon concentration (%C), specific leaf area (SLA), leaf dry matter content (LDMC), leaf area (LA). In addition they included three whole-plant traits: tree height (H), crown cross-sectional area (CCSA), and diameter-at-breast-height (DBH). We applied partial least squares regression using Sentinel-2 surface reflectance measured in 2015 as predictive variables to model in-situ FDis measurements. We predicted, in cross-validation, 55% of the variation in the observed FDis. We also showed that the red-edge, near infrared and shortwave infrared regions of Sentinel-2 are more important than the visible region for predicting FDis. An initial 30-m resolution mapping of FDis revealed large local FDis variation within each forest type. The novelty of this study is the effective integration of spaceborne and in-situ measurements at a continental scale, and hence represents a key step towards achieving rapid global biodiversity monitoring schemes., This work was primarily supported by an iDiv-Flexpool project “Observing effects of biodiversity on ecosystem functioning across time, space, and wavelength: oBEF-Across” and a European Union H2020 project “Detecting changes in essential ecosystem and biodiversity properties - towards a Biosphere Atmosphere Change Index: BACI” (grant agreement number: 640176). The data from FunDivEUROPE network was collected with the financial support from the European Union Seventh Framework Programme (FP7/2007-2013) (grant agreement number: 265171). Remeasurements across all FunDivEUROPE plots were financed by EU H2020 project Soil4Europe (Bioidversa 2017-2019). We thank Prof. Dr. Michael Scherer-Lorenzen and Prof. Dr. Kris Verheyen from FunDivEUROPE network for their generous help with field data during the paper revision. DEPM and MM and MDM also acknowledge the support of the Trustee European Commission project no H2020-MSCA-ITN-2016 – 721995. The free use of Sentinel-2 data is enabled by ESA's Copernicus Open Access Hub. The in-situ plant traits data collected over Finnish, Romanian, and Spanish sites were supported by a Marie-Curie Fellowship (DIVERFOR, FP7-PEOPLE-2011-IEF. No. 302445) to R. Benavides. The free access of plant trait data was supported by the TRY initiative (http://www.try-db.org)

Progressing land degradation is of increasing global concern because it deteriorates essential ecosystem features, functions, and services as observed in our study area in the highly fragmented Mata Atlântica biome, RJ, Brazil. The prioritization of sites for land rehabilitation is a frequent task for environmental managers and essential to develop urgently needed public policies. Hence, we present a GIS-based tool based on ecological principles for the selection of reforestation sites by integrating data on pasture degradation and landscape fragmentation. Thereby, the prioritized areas do not only represent opportunities for increasing forest cover and enhancing forest connectivity but also for reducing the area of degraded pastures. From our perspective, the inclusion of spatial information on degraded pastures is essential, since many of these areas have lost important ecological and economic function and should thus be prioritized for intervention. Data on degraded pastures and forest cover used in this study are derived from high- and medium-resolution satellite imagery. Other spatial data are derived from a digital elevation model (DEM) with 20 m resolution. The multicriteria analysis for the data integration was conducted using ESRI ArcGIS and the open-source software ILWIS.

In this article we describe applications of Discrete Differential Forms in computational GR. In particular we consider the initial value problem in vacuum space-times that are spherically symmetric. The motivation to investigate this method is mainly its manifest coordinate independence. Three numerical schemes are introduced, the results of which are compared with the corresponding analytic solutions. The error of two schemes converges quadratically to zero. For one scheme the errors depend strongly on the initial data., 22 pages, 6 figures, accepted by Class. Quant. Grav

We study properties of evolution equations which are first order in time and arbitrary order in space (FTNS). Following Gundlach and Mart\'in-Garc\'ia (2006) we define strong and symmetric hyperbolicity for FTNS systems and examine the relationship between these definitions, and the analogous concepts for first order systems. We demonstrate equivalence of the FTNS definition of strong hyperbolicity with the existence of a strongly hyperbolic first order reduction. We also demonstrate equivalence of the FTNS definition, up to N=4, of symmetric hyperbolicity with the existence of a symmetric hyperbolic first order reduction., Comment: 33 pages

We consider gauge theories from the free evolution point of view, in which initial data satisfying constraints of a theory are given, and because the constraints satisfy a closed evolution system, they remain so. We study a model constrained Hamiltonian theory and identify a particular structure in the equations of motion which we call the standard gauge freedom. The pure gauge subsystem of this model theory is identified, and the manner in which the gauge variables couple to the field equations is presented. We demonstrate that the set of gauge choices that can be coupled to the field equations to obtain a strongly hyperbolic formulation is exactly the set of strongly hyperbolic pure gauges. Consequently we analyze a parametrized family of formulations of general relativity. The generalization of the harmonic gauge formulation to a five parameter family of gauge conditions is obtained.

With the aim of deriving symmetric hyperbolic free-evolution systems for GR that possess Hamiltonian structure and allow for the popular puncture gauge condition we analyze the hyperbolicity of Hamiltonian systems. We develop helpful tools which are applicable to either the first order in time, second order in space or the fully second order form of the equations of motion. For toy models we find that the Hamiltonian structure can simplify the proof of symmetric hyperbolicity. In GR we use a special structure of the principal part to prove symmetric hyperbolicity of a formulation that includes gauge conditions which are very similar to the puncture gauge., Comment: Our mathematica scripts are available at http://na.mathematik.uni-tuebingen.de/~richter/

We describe how we use symplectic time integrators in numerical general relativity. Of particular interest is the free symplectic Stormer‐Verlet method and its application to the dynamical part of ADM‐like equations.The behavior of this scheme is illustrated on an effectively 1+1‐dimensional version of Einstein’s equations that we apply to a perturbed Minkowski problem. We discuss differences between symplectic and non‐symplectic integrators, showing favorable evolution properties of the symplectic Stormer‐Verlet method in this example.To handle the constraint part of the equations with a symplectic integrator one can use a partially constrained scheme that applies the RATTLE method, a modification of the Stormer‐Verlet method for holonomic constraints.

Well-posedness of the initial (boundary) value problem is an essential property, both of meaningful physical models and of numerical applications. To prove well-posedness of wave-type equations their level of hyperbolicity is an essential ingredient. We develop helpful tools and classify a large class of Hamiltonian versions of Einstein's equations with live gauge conditions with respect to their hyperbolicity. Finally we find a symmetric hyperbolic Hamiltonian formulation that allows for gauge conditions which are similar to the puncture gauge., Proceedings of the Spanish Relativity Meeting ERE 2010

We consider two strongly hyperbolic Hamiltonian formulations of general relativity and their numerical integration with a free and a partially constrained symplectic integrator. In those formulations we use hyperbolic drivers for the shift and in one case also for the densitized lapse. A system where the densitized lapse is an external field allows to enforce the momentum constraints in a holonomically constrained Hamiltonian system and to turn the Hamilton constraint function from a weak to a strong invariant. These schemes are tested in a perturbed Minkowski and the Schwarzschild space-time. In those examples we find advantages of the strongly hyperbolic formulations over the ADM system presented in [arXiv:0807.0734]. Furthermore we observe stabilizing effects of the partially constrained evolution in Schwarzschild space-time as long as the momentum constraints are enforced., This version clarifies some points concerning the interpretation of the results

We consider symplectic time integrators in numerical General Relativity and discuss both free and constrained evolution schemes. For free evolution of ADM-like equations we propose the use of the Stoermer-Verlet method, a standard symplectic integrator which here is explicit in the computationally expensive curvature terms. For the constrained evolution we give a formulation of the evolution equations that enforces the momentum constraints in a holonomically constrained Hamiltonian system and turns the Hamilton constraint function from a weak to a strong invariant of the system. This formulation permits the use of the constraint-preserving symplectic RATTLE integrator, a constrained version of the Stoermer-Verlet method. The behavior of the methods is illustrated on two effectively 1+1-dimensional versions of Einstein's equations, that allow to investigate a perturbed Minkowski problem and the Schwarzschild space-time. We compare symplectic and non-symplectic integrators for free evolution, showing very different numerical behavior for nearly-conserved quantities in the perturbed Minkowski problem. Further we compare free and constrained evolution, demonstrating in our examples that enforcing the momentum constraints can turn an unstable free evolution into a stable constrained evolution. This is demonstrated in the stabilization of a perturbed Minkowski problem with Dirac gauge, and in the suppression of the propagation of boundary instabilities into the interior of the domain in Schwarzschild space-time., 25 pages, 7 figures; This version contains minor clarifications and corrections