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Recent outbreaks of the European spruce bark beetle (Ips typographus) in Norway spruce (Picea abies) forests in Central Europe highlight the importance of timely detection and sanitation of infested trees for pest management efficacy. This study provides novel quantitative evidence on the manifestation of infestation symptoms and their visual detectability, to guide accelerated, optimized terrestrial bark beetle monitoring, as well as establishing benchmarks for potential alternative (e.g. sensor-based) monitoring approaches. We employed bi-weekly, individual tree-level assessments on 85 hectares of spruce-dominated unmanaged forest over a 2-year period in south-western Germany (detecting a total of 1,176 infested trees). By applying decision tree-type models, we quantified the predictive power of observed symptoms and their correlation with environmental factors and time. Terrestrial detection accuracy and timeliness were high, suggestive of being sufficient to suppress I. typographus outbreak propagation by subsequent sanitation felling. Among the six studied symptoms, boring dust occurred most frequently (in 82% of correctly detected infestations) and is most suitable for timely detection. Total symptom abundance was best explained by two site parameters (slope, Standardized Precipitation-Evapotranspiration-Index) and I. typographus population density, while it was widely independent of tree parameters and time. Though individual symptoms varied over time and among trees, patterns were clearly identified. For instance, infestations in spring were most critical to be timely detected, while increasing crown discoloration and defoliation facilitated detection in late summer and autumn. Findings further imply that hibernation trees would optimally be detected already in late summer with sanitation felling applied before November.

Of the > 6000 species of bark beetles (Coleoptera: Curculionidae, Scolytinae), ~ 25 species cause significant amounts of tree mortality in conifer-dominated forests. Several tactics are available to manage bark beetle infestations and to reduce associated levels of tree mortality. Suppression involves short-term tactics designed to address current infestations by manipulating beetle populations and typically includes the use of sanitation harvests, insecticides, semiochemicals, or a combination of these and other treatments. Prevention is designed to reduce the probability and severity of future infestations by manipulating stand, forest, and/or landscape conditions by reducing the number of susceptible hosts through thinning, prescribed burning, and/or altering age classes and species compositions. In this chapter, we review the ecology and management of bark beetles in conifer-dominated forests in North America and Europe, where they exert their largest impacts, and provide six case studies focused on the effects of altered forest and climatic conditions on bark beetle ecology and management. We conclude that in many forests bark beetle outbreaks have and will continue to be exacerbated by climate change due to shifts in temperature and precipitation that influence bark beetles, their hosts, and community associates. Changes in forest structure and composition by natural processes and management practices have and will continue to be important factors as well. As a result, natural resource managers will be increasingly challenged to manage bark beetle populations, and to facilitate recovery of landscapes impacted by bark beetle outbreaks. In most cases, current management tactics are based on research and development executed in the 20th century and unable to meet the demands imposed by altered forest and climatic conditions without some modification and/or adaptation.

Our study suggests that the global CO 2 fertilization effect (CFE) on vegetation photosynthesis has declined during the past four decades. The Comments suggest that the temporal inconsistency in AVHRR data and the attribution method undermine the results’ robustness. Here, we provide additional evidence that these arguments did not affect our finding and that the global decline in CFE is robust.

Drought has promoted large-scale, insect-induced tree mortality in recent years, with severe consequences for ecosystem function, atmospheric processes, sustainable resources and global biogeochemical cycles. However, the physiological linkages among drought, tree defences, and insect outbreaks are still uncertain, hindering our ability to accurately predict tree mortality under on-going climate change. Here we propose an interdisciplinary research agenda for addressing these crucial knowledge gaps. Our framework includes field manipulations, laboratory experiments, and modelling of insect and vegetation dynamics, and focuses on how drought affects interactions between conifer trees and bark beetles. We build upon existing theory and examine several key assumptions: (1) there is a trade-off in tree carbon investment between primary and secondary metabolites (e.g. growth vs defence); (2) secondary metabolites are one of the main component of tree defence against bark beetles and associated microbes; and (3) implementing conifer-bark beetle interactions in current models improves predictions of forest disturbance in a changing climate. Our framework provides guidance for addressing a major shortcoming in current implementations of large-scale vegetation models, the under-representation of insect-induced tree mortality.

Forest disturbances that lead to the replacement of whole tree stands are a cornerstone of forest dynamics, with drivers that include fire, windthrow, biotic outbreaks and harvest. The frequency of disturbances may change over the next century with impacts on the age, composition and biomass of forests. However, the disturbance return time, that is, the mean interval between disturbance events, remains poorly characterized across the world’s forested biomes, which hinders the quantification of the role of disturbances in the global carbon cycle. Here we present the global distribution of stand-replacing disturbance return times inferred from satellite-based observations of forest loss. Prescribing this distribution within a vegetation model with a detailed representation of stand structure, we quantify the importance of stand-replacing disturbances for biomass carbon turnover globally over 2001–2014. The return time varied from less than 50 years in heavily managed temperate ecosystems to over 1,000 years in tropical evergreen forests. Stand-replacing disturbances accounted for 12.3% (95% confidence interval, 11.4–13.7%) of the annual biomass carbon turnover due to tree mortality globally, and in 44% of the forested area, biomass stocks are strongly sensitive to changes in the disturbance return time. Relatively small shifts in disturbance regimes in these areas would substantially influence the forest carbon sink that currently limits climate change by offsetting emissions. Forest stand-replacing disturbances significantly affect the biomass stocks in about a half of forested area globally, according to analyses of global forest loss from satellite data, together with a dynamic vegetation model.

Variability in climate exerts a strong influence on vegetation productivity (gross primary productivity; GPP), and therefore has a large impact on the land carbon sink. However, no direct observations of global GPP exist, and estimates rely on models that are constrained by observations at various spatial and temporal scales. Here, we assess the consistency in GPP from global products which extend for more than three decades; two observation‐based approaches, the upscaling of FLUXNET site observations (FLUXCOM) and a remote sensing derived light use efficiency model (RS‐LUE), and from a suite of terrestrial biosphere models (TRENDYv6). At local scales, we find high correlations in annual GPP among the products, with exceptions in tropical and high northern latitudes. On longer time scales, the products agree on the direction of trends over 58% of the land, with large increases across northern latitudes driven by warming trends. Further, tropical regions exhibit the largest interannual variability in GPP, with both rainforests and savannas contributing substantially. Variability in savanna GPP is likely predominantly driven by water availability, although temperature could play a role via soil moisture‐atmosphere feedbacks. There is, however, no consensus on the magnitude and driver of variability of tropical forests, which suggest uncertainties in process representations and underlying observations remain. These results emphasize the need for more direct long‐term observations of GPP along with an extension of in situ networks in underrepresented regions (e.g., tropical forests). Such capabilities would support efforts to better validate relevant processes in models, to more accurately estimate GPP., Key Points Changes in climate over the period 1982–2016 have increased GPP at a global scale and across northern latitudesSavannas and tropical forests are hotspots for IAV in GPP, although the dominant climate drivers are not consistent among the assessed productsDGVMs systematically underestimate the IAV of GPP in tropical forests, highlighting the need for improved parameterizations/formulations

Changes in vegetation structure are expected to influence the redistribution of heat and moisture; however, how variations in the leaf area index (LAI) affect this global energy partitioning is not yet quantified. Here, we estimate that a unit change in LAI leads to 3.66 ± 0.45 and −3.26 ± 0.41 W m−2 in latent (LE) and sensible (H) fluxes, respectively, over the 1982–2016 period. Analysis of an ensemble of data-driven products shows that these sensitivities increase by about 20% over the observational period, prominently in regions with a limited water supply, probably because of an increased transpiration/evaporation ratio. Global greening has caused a decrease in the Bowen ratio (B = H/LE) of −0.010 ± 0.002 per decade, which is attributable to the increased evaporative surface. Such a direct LAI effect on energy fluxes is largely modulated by plant functional types (PFTs) and background climate conditions. Land surface models (LSMs) misrepresent this vegetation control, possibly due to underestimation of the biophysical responses to changes in the water availability and poor representation of LAI dynamics. Changes in the leaf area index alter the distribution of heat and moisture. The change in energy partitioning related to leaf area, increasing latent and decreasing sensible fluxes over the observational period 1982–2016, is moderated by plant functional type and background climate.

A decline in the carbon fertilization effect One source of uncertainty in climate science is how the carbon fertilization effect (CFE) will contribute to mitigation of anthropogenic climate change. Wang et al. explored the temporal dynamics of CFE on vegetation photosynthesis at the global scale. There has been a decline over recent decades in the contribution of CFE to vegetation photosynthesis, perhaps owing to the limiting effects of plant nutrients such as nitrogen and phosphorus. This declining trend has not been adequately accounted for in carbon cycle models. CFE thus has limitations for long-term mitigation of climate change, and future warming might currently be underestimated. Science , this issue p. 1295

International audience; Robust estimates of CO2 budget, CO2 exchanged between the atmosphere and terrestrial biosphere, are necessary to better understand the role of the terrestrial biosphere in mitigating anthropogenic CO2 emissions. Over the past decade, this field of research has advanced through understanding of the differences and similarities of two fundamentally different approaches: “top-down” atmospheric inversions and “bottom-up” biosphere models. Since the first studies were undertaken, these approaches have shown an increasing level of agreement, but disagreements in some regions still persist, in part because they do not estimate the same quantity of atmosphere–biosphere CO2 exchange. Here, we conducted a thorough comparison of CO2 budgets at multiple scales and from multiple methods to assess the current state of the science in estimating CO2 budgets. Our set of atmospheric inversions and biosphere models, which were adjusted for a consistent flux definition, showed a high level of agreement for global and hemispheric CO2 budgets in the 2000s. Regionally, improved agreement in CO2 budgets was notable for North America and Southeast Asia. However, large gaps between the two methods remained in East Asia and South America. In other regions, Europe, boreal Asia, Africa, South Asia, and Oceania, it was difficult to determine whether those regions act as a net sink or source because of the large spread in estimates from atmospheric inversions. These results highlight two research directions to improve the robustness of CO2 budgets: (a) to increase representation of processes in biosphere models that could contribute to fill the budget gaps, such as forest regrowth and forest degradation; and (b) to reduce sink–source compensation between regions (dipoles) in atmospheric inversion so that their estimates become more comparable. Advancements on both research areas will increase the level of agreement between the top-down and bottom-up approaches and yield more robust knowledge of regional CO2 budgets.

Climate change is shifting the phenological cycles of plants1, thereby altering the functioning of ecosystems, which in turn induces feedbacks to the climate system2. In northern (north of 30° N) ecosystems, warmer springs lead generally to an earlier onset of the growing season3,4 and increased ecosystem productivity early in the season5. In situ6 and regional7–9 studies also provide evidence for lagged effects of spring warmth on plant productivity during the subsequent summer and autumn. However, our current understanding of these lagged effects, including their direction (beneficial or adverse) and geographic distribution, is still very limited. Here we analyse satellite, field-based and modelled data for the period 1982–2011 and show that there are widespread and contrasting lagged productivity responses to spring warmth across northern ecosystems. On the basis of the observational data, we find that roughly 15 per cent of the total study area of about 41 million square kilometres exhibits adverse lagged effects and that roughly 5 per cent of the total study area exhibits beneficial lagged effects. By contrast, current-generation terrestrial carbon-cycle models predict much lower areal fractions of adverse lagged effects (ranging from 1 to 14 per cent) and much higher areal fractions of beneficial lagged effects (ranging from 9 to 54 per cent). We find that elevation and seasonal precipitation patterns largely dictate the geographic pattern and direction of the lagged effects. Inadequate consideration in current models of the effects of the seasonal build-up of water stress on seasonal vegetation growth may therefore be able to explain the differences that we found between our observation-constrained estimates and the model-constrained estimates of lagged effects associated with spring warming. Overall, our results suggest that for many northern ecosystems the benefits of warmer springs on growing-season ecosystem productivity are effectively compensated for by the accumulation of seasonal water deficits, despite the fact that northern ecosystems are thought to be largely temperature- and radiation-limited10.

International audience; Gaps in our current understanding and quantification of biomass carbon stocks, particularly in tropics, lead to large uncertainty in future projections of the terrestrial carbon balance. We use the recently published GlobBiomass data set of forest above-ground biomass (AGB) density for the year 2010, obtained from multiple remote sensing and in situ observations at 100 m spatial resolution to evaluate AGB estimated by nine dynamic global vegetation models (DGVMs). The global total forest AGB of the nine DGVMs is 365 ± 66 Pg C, the spread corresponding to the standard deviation between models, compared to 275 Pg C with an uncertainty of ~13.5% from GlobBiomass. Model-data discrepancy in total forest AGB can be attributed to their discrepancies in the AGB density and/or forest area. While DGVMs represent the global spatial gradients of AGB density reasonably well, they only have modest ability to reproduce the regional spatial gradients of AGB density at scales below 1000 km. The 95th percentile of AGB density (AGB95) in tropics can be considered as the potential maximum of AGB density which can be reached for a given annual precipitation. GlobBiomass data show local deficits of AGB density compared to the AGB95, particularly in transitional and/or wet regions in tropics. We hypothesize that local human disturbances cause more AGB density deficits from GlobBiomass than from DGVMs, which rarely represent human disturbances. We then analyse empirical relationships between AGB density deficits and forest cover changes, population density, burned areas and livestock density. Regression analysis indicated that more than 40% of the spatial variance of AGB density deficits in South America and Africa can be explained; in Southeast Asia, these factors explain only ~25%. This result suggests TRENDY v6 DGVMs tend to underestimate biomass loss from diverse and widespread anthropogenic disturbances, and as a result overestimate turnover time in AGB.

Forest disturbances are sensitive to climate. However, our understanding of disturbance dynamics in response to climatic changes remains incomplete, particularly regarding large-scale patterns, interaction effects and dampening feedbacks. Here we provide a global synthesis of climate change effects on important abiotic (fire, drought, wind, snow and ice) and biotic (insects and pathogens) disturbance agents. Warmer and drier conditions particularly facilitate fire, drought and insect disturbances, while warmer and wetter conditions increase disturbances from wind and pathogens. Widespread interactions between agents are likely to amplify disturbances, while indirect climate effects such as vegetation changes can dampen long-term disturbance sensitivities to climate. Future changes in disturbance are likely to be most pronounced in coniferous forests and the boreal biome. We conclude that both ecosystems and society should be prepared for an increasingly disturbed future of forests. © 2017 Macmillan Publishers Limited, part of Springer Nature. All rights reserved.

Aim Biotic disturbances (BD, including insects, pathogens and wildlife herbivory) can alter forest structure and the capability of forests to deliver ecosystem services. Impact assessments, however, are limited by the lack of reliable and timely disturbance data at large spatial scales. This review synthesizes empirical data on the magnitude and distribution of spatio-temporal impacts of BD. Location Northern Hemisphere. Methods Based on large-scale, multi-year BD data sets, covering c. 46% of the global forest, we calculated annual disturbance fractions Df (percentage of forest area affected) and their inter-annual variability at a grid cell resolution of 1°. The impact of BD on forest carbon pools was determined by overlaying Df with data on forest cover and carbon density. Results Overall, 43.9 million hectares (Mha) (Df = 2.6%) of forests were affected annually by BD, particularly by insects (36.5 Mha, Df = 2.2%). Our synthesis demonstrates that fractions affected by BD (1) vary greatly over space and time, mainly in response to ephemeral bark beetle and defoliator outbreaks, (2) show temporal trends that are inconsistent across regions, yet are largely increasing over recent decades, and (3) are substantially higher than Df caused by fire and other abiotic disturbances. Tree mortality was estimated over an area of 3.3 Mha year−1 (medium estimate which assumed mortality at 7.5% of the affected area), with associated committed carbon fluxes from living biomass to litter and the atmosphere at 129.9 Mt C year−1. Main conclusions BD are key drivers of forest dynamics, making a contribution to tree mortality of a similar magnitude to fire. Despite inherent uncertainties, the data reported can be used to improve the representation of BD in global ecosystem models. Our findings call for future forest monitoring approaches to provide accessible, precise and consistent data on the occurrence and severity of BD which are harmonized across jurisdictions.

Climate extremes have remarkable impacts on ecosystems and are expected to increase with future global warming. However, only few studies have focused on the ecological extreme events and their drivers in China. In this study, we carried out an analysis of negative extreme events in gross primary productivity (GPP) in China and the sub-regions during 1982–2015, using monthly GPP simulated by 12 process-based models (TRENDYv6) and an observation-based model (Yao-GPP). Extremes were defined as the negative 5th percentile of GPP anomalies, which were further merged into individual extreme events using a three-dimensional contiguous algorithm. Spatio-temporal patterns of negative GPP anomalies were analyzed by taking the 1000 largest extreme events into consideration. Results showed that the effects of extreme events decreased annual GPP by 2.8% (i.e. 208 TgC year−1) in TRENDY models and 2.3% (i.e. 151 TgC year−1) in Yao-GPP. Hotspots of extreme GPP deficits were mainly observed in North China (−53 gC m−2 year−1) in TRENDY models and Northeast China (−42 gC m−2 year−1) in Yao-GPP. For China as a whole, attribution analyses suggested that extreme low precipitation was associated with 40%–50% of extreme negative GPP events. Most events in northern and western China could be explained by meteorological droughts (i.e. low precipitation) while GPP extreme events in southern China were more associated with temperature extremes, in particular with cold spells. GPP was revealed to be much more sensitive to heat/drought than to cold/wet extreme events. Combined with projected changes in climate extremes in China, GPP negative anomalies caused by drought events in northern China and by temperature extremes in southern China might be more prominent in the future.

Climate change is shifting the phenological cycles of plants

International audience; nitori Accumulating evidence highlights increased mortality risks for trees during severe drought, particularly under warmer temperatures and increasing vapour pressure deficit (VPD). Resulting forest die-off events have severe consequences for ecosystem services, biophysical and biogeochemical land-atmosphere processes. Despite advances in monitoring, modelling and experimental studies of the causes and consequences of tree death from individual tree to ecosystem and global scale, a general mechanistic understanding and realistic predictions of drought mortality under future climate conditions are still lacking. We update a global tree mortality map and present a roadmap to a more holistic understanding of forest mortality across scales. We highlight priority research frontiers that promote: (1) new avenues for research on key tree ecophysiological responses to drought; (2) scaling from the tree/plot level to the ecosystem and region; (3) improvements of mortality risk predictions based on both empirical and mechanistic insights; and (4) a global mong network of forest mortality. In light of recent and anticipated large forest die-off events such a research agenda is timely and needed to achieve scientific understanding for realistic predictions of drought-induced tree mortality. The implementation of a sustainable network will require support by stakeholders and political authorities at the international level.

Land Surface Models (LSMs) are essential to reproduce biophysical processes modulated by vegetation and to predict the future evolution of the land‐climate system. To assess the performance of an ensemble of LSMs (JSBACH, JULES, ORCHIDEE, CLM, and LPJ‐GUESS) a consistent set of land surface energy fluxes and leaf area index (LAI) has been generated. Relationships of interannual variations of modeled surface fluxes and LAI changes have been analyzed at global scale across climatological gradients and compared with those obtained from satellite‐based products. Model‐specific strengths and deficiencies were diagnosed for tree and grass biomes. Results show that the responses of grasses are generally well represented in models with respect to the observed interplay between turbulent fluxes and LAI, increasing the confidence on how the LAI‐dependent partition of net radiation into latent and sensible heat are simulated. On the contrary, modeled forest responses are characterized by systematic bias in the relation between the year‐to‐year variability in LAI and net radiation in cold and temperate climates, ultimately affecting the amount of absorbed radiation due to LAI‐related effects on surface albedo. In addition, for tree biomes, the relationships between LAI and turbulent fluxes appear to contradict the experimental evidences. The dominance of the transpiration‐driven over the observed albedo‐driven effects might suggest that LSMs have the incorrect balance of these two processes. Such mismatches shed light on the limitations of our current understanding and process representation of the vegetation control on the surface energy balance and help to identify critical areas for model improvement., Key Points The covariability of land biophysics and changes in vegetation density predicted by Land Surface Models is compared with satellite dataBiophysical properties of vegetation are explored across climatological gradients of temperature and precipitationModel‐specific and systematic strengths and deficiencies are diagnosed separately for tree and grass biomes

Field measurements of aboveground net primary productivity (ANPP) in temperate grasslands suggest that both positive and negative asymmetric responses to changes in precipitation (P) may occur. Under normal range of precipitation variability, wet years typically result in ANPP gains being larger than ANPP declines in dry years (positive asymmetry), whereas increases in ANPP are lower in magnitude in extreme wet years compared to reductions during extreme drought (negative asymmetry). Whether the current generation of ecosystem models with a coupled carbon–water system in grasslands are capable of simulating these asymmetric ANPP responses is an unresolved question. In this study, we evaluated the simulated responses of temperate grassland primary productivity to scenarios of altered precipitation with 14 ecosystem models at three sites: Shortgrass steppe (SGS), Konza Prairie (KNZ) and Stubai Valley meadow (STU), spanning a rainfall gradient from dry to moist. We found that (1) the spatial slopes derived from modeled primary productivity and precipitation across sites were steeper than the temporal slopes obtained from inter-annual variations, which was consistent with empirical data; (2) the asymmetry of the responses of modeled primary productivity under normal inter-annual precipitation variability differed among models, and the mean of the model ensemble suggested a negative asymmetry across the three sites, which was contrary to empirical evidence based on filed observations; (3) the mean sensitivity of modeled productivity to rainfall suggested greater negative response with reduced precipitation than positive response to an increased precipitation under extreme conditions at the three sites; and (4) gross primary productivity (GPP), net primary productivity (NPP), aboveground NPP (ANPP) and belowground NPP (BNPP) all showed concave-down nonlinear responses to altered precipitation in all the models, but with different curvatures and mean values. Our results indicated that most models overestimate the negative drought effects and/or underestimate the positive effects of increased precipitation on primary productivity under normal climate conditions, highlighting the need for improving eco-hydrological processes in those models in the future.

1. Unprecedented bark beetle outbreaks have been observed for a variety of forest ecosystems recently, and damage is expected to further intensify as a consequence of climate change. In Central Europe, the response of ecosystem management to increasing infestation risk has hitherto focused largely on the stand level, while the contingency of outbreak dynamics on large-scale drivers remains poorly understood. 2. To investigate how factors beyond the local scale contribute to the infestation risk from Ips typographus (Col., Scol.), we analysed drivers across seven orders of magnitude in scale (from 103 to 1010 m2) over a 23-year period, focusing on the Bavarian Forest National Park. Time-discrete hazard modelling was used to account for local factors and temporal dependencies. Subsequently, beta regression was applied to determine the influence of regional and landscape factors, the latter characterized by means of graph theory. 3. We found that in addition to stand variables, large-scale drivers also strongly influenced bark beetle infestation risk. Outbreak waves were closely related to landscape-scale connectedness of both host and beetle populations as well as to regional bark beetle infestation levels. Furthermore, regional summer drought was identified as an important trigger for infestation pulses. Large-scale synchrony and connectivity are thus key drivers of the recently observed bark beetle outbreak in the area. 4.Synthesis and applications. Our multiscale analysis provides evidence that the risk for biotic disturbances is highly dependent on drivers beyond the control of traditional stand-scale management. This finding highlights the importance of fostering the ability to cope with and recover from disturbance. It furthermore suggests that a stronger consideration of landscape and regional processes is needed to address changing disturbance regimes in ecosystem management.

Biotic disturbances (BDs, e.g., insects, pathogens and wildlife herbivory) substantially affect boreal and temperate forest ecosystems globally. However, accurate impact assessments comprising larger spatial scales are lacking to date, although these are critically needed given the expected disturbance intensification under a warming climate. Hence, our quantitative knowledge on current and future BD impacts, e.g., on forest carbon (C) cycling, is strongly limited. We extended a Dynamic Global Vegetation Model to simulate ecosystem response to prescribed tree mortality and defoliation due to multiple biotic agents across United States forests during the period 1997-2015, and quantified the BD-induced vegetation C loss, i.e., C fluxes from live vegetation to dead organic matter pools. Annual disturbance fractions separated by BD type (tree mortality and defoliation) and agent (bark beetles, defoliator insects, other insects, pathogens, and other biotic agents) were calculated at 0.5° resolution from aerial-surveyed data and applied within the model. Simulated BD-induced C fluxes totaled 251.6 Mt C (annual mean: 13.2 Mt C yr−1, SD ±7.3 Mt C yr−1 between years) across the study domain, to which tree mortality contributed 95% and defoliation 5%. Among BD agents, bark beetles caused most C fluxes (61%), and total insect-induced C fluxes were about five times larger compared to non-insect agents, e.g., pathogens and wildlife. Our findings further demonstrate that BD-induced C cycle impacts (i) displayed high spatio-temporal variability, (ii) were dominated by different agents across BD types and regions, and (iii) were comparable in magnitude to fire-induced impacts. This study provides the first ecosystem model-based assessment of BD-induced impacts on forest C cycling at the continental scale and going beyond single agent-host systems, thus allowing for comparisons across regions, BD types and agents. Ultimately, a perspective on the potential and limitations of a more process-based incorporation of multiple BDs in ecosystem models is offered. This article is protected by copyright. All rights reserved.

Bark beetles are among the main biotic hazards affecting forests worldwide. Aerial surveys are an appropriate and commonly used tool for detecting and monitoring bark beetle infestations at the landscape scale. However, a considerable time-lag in the aerial-surveyed data limits its use, e.g. for analyses which include temporary factors. This temporal lag is caused by the gradual decay of the host tree following a bark beetle attack. A change in the spectral signature in aerial imagery indicates an attack with a delay of several weeks or even months. Thus, aerial-surveyed infestation data suffer a temporal shift, i.e. infestations detected for a specific time period cannot be directly assumed to have been initiated within that same period. The present study introduces an algorithm which assigns the most probable time of Ips typographus L. attack to infestations detected by aerial surveys. To calculate the infestations initiated within a certain year x the algorithm considers the potential attack period, the assumed time-lag, as well as the date of aerial surveys and the amount of detected infestation from the years x, x − 1 and x + 1. The deviation between infestations detected by aerial survey and those actually initiated (as calculated by the algorithm) quantifies the correction effect, i.e. the time-lag bias. The algorithm was then applied to a data set which covers a time series of 26 consecutive years, including both managed and non-managed infestations. To account for uncertainty in the input variables or to mimic varying environments the application considers three different scenarios. Over all three scenarios results indicate substantial deviations, which may be either positive or negative. Further, deviation is shown to be affected by the length of the time-lag and the attack period, as well as by variations in survey dates and infestation frequency of consecutive years. Finally, the time-corrected infestation data provides a threefold benefit: (i) The temporal pattern of oscillating population dynamics is truly reflected. (ii) Comprehensive correlation analyses which include dynamic environmental covariates, e.g. temperature, precipitation, or antagonists, are facilitated. (iii) Aerial-surveyed and ground-surveyed monitoring data can be easily related whether within a region or between regions. In conclusion, this study increases the value of aerial-surveyed infestation data for bark beetle monitoring and research.

Tree-killing bark beetle species such as Ips sp. and Dendroctonus sp. are considered one of the most severe biotic hazards affecting forests at the global scale. Although spatio-temporal patterns of dispersal and infestations have been widely observed and statistically analyzed profound knowledge about the host–bark beetle interactions that evoke these patterns is scarce. We developed an individual-based and spatially explicit model – the Infestation Pattern Simulation (IPS) model – to elucidate how individual traits affect system-level dispersal and infestation patterns. IPS simulates processes including dispersal, host selection, aggregation, and finally colonization, or rejection by host defence on a local scale. Host–bark beetle interactions are implemented highly dynamically, i.e. individual adaptive behavior takes into account space- and time-dependent variations in traits. Simulations consider one dispersal wave starting from a single source located in a virtual stand. Finally, the effects of both bark beetle- and host tree-specific parameters on emerging system patterns were quantified using a one-factor-at-a-time sensitivity analysis approach. As system-level response variables we used (i) percentage of successful beetles, (ii) number of infestations, and (iii) maximum infestation distance to source. Among bark beetle-specific parameters those affecting host recognition (e.g. perceptual range, energetic level) and attack synchrony (e.g. source size, time lag between flight cohorts) were revealed to be highly sensitive with regard to all three response variables. In addition, the host tree's resistance and spatial distribution is also shown to be decisive for infestation occurrence. The model provides a conceptual framework linking individual behavior to system-level patterns. Thus it represents a powerful tool – complementing lab- and field-based approaches – which may contribute to our understanding of the complex spatio-temporal processes that govern host–bark beetle dynamics.

Large areas of mangrove forests were devastated in South Viet Nam during the second Indochina war. After its end in 1975, extensive reforestation with monocultures took place. Can Gio, one of the biggest replanted sites with about 20,000 ha of mangroves mainly Rhizophora apiculata , was declared a biosphere reserve by the UNESCO in 2000. Although this status now enables progressive forest dynamics, there are still drawbacks resulting from the unnatural character of the plantations. For example, the homogeneous size and age structure as well as the regular arrangement of the planted trees make larger forest stands more vulnerable to synchronized collapsing which can be triggered by stronger winds and storms. A transformation into a more natural forest characterized by a heterogeneous age and size structure and a mixed species composition is of urgent need to avoid a synchronized dieback. In this study we test the capability of natural canopy disturbances (e.g. lightning strikes) to facilitate this transformation. Canopy gaps created by lightning strikes were detected and quantified by remote sensing techniques. SPOT satellite images from the years 2003, 2005 and 2007 provided information about the spatial distribution, size, shape, and formation frequency of the gaps. Lightning strike gaps were identified based on their shape and size. They form small openings (mean: 0.025 ha) and their yearly probability of occurrence was determined to be approximately 0.012 per hectare. Selected gaps were surveyed in the field in 2008 to complement the remote sensing data and to provide information upon forest structure and regeneration. Simulation experiments were carried out with the individual-based KiWi mangrove model for quantifying the influence of different lightning regimes on the vertical and horizontal structure of the R. apiculata plantation. In addition, we conducted simulations with a natural and thus randomly generated forest to compare the structure of the two different cultivation types (i.e. plantation and natural forest). The simulation shows that even small disturbances can already partly buffer the risk of cohort senescence of monospecific even-aged plantations. However, after the decline of the plantation, the disturbance regime does not play an important role for further stand development. After the break-up of the initial strongly regular structure of the simulated plantation, a vertical pattern, i.e. height distribution of the trees, similar to the one of the natural forest, emerged quickly. However, the convergence for the horizontal structure i.e. the distance of trees to their nearest neighbor, took twice as long as for the vertical structure. Our results highlight the importance of small disturbances such as lightning strikes to mitigate vulnerability against synchronous windfall in homogenous forest structures. Hence, creating small openings artificially may be an appropriate management measure in areas where the frequency of natural small-scale disturbances is low.

Bark beetle dispersal and host selection behaviour are a complex and poorly understood process, resulting in specific spatio-temporal infestation patterns in forests. Aerial images from the Bavarian Forest National Park (Germany) provide a high-resolution, that is, tree-scale data set for the period 2001–2010, including information about Ips typographus (Col., Curculio., Scolytinae) infestation, the application of sanitary logging, natural forest edges and the area of living spruce susceptible to bark beetle infestation. We combined methods of GIS and image analysis to investigate the infestation probabilities at three types of forest edges under spatial and temporal aspects and compared them to the corresponding probabilities at the stand interior. Our results showed a pronounced infestation predisposition of such edge trees delimiting infestation patches cleared by sanitary logging measures, in particular at the south-facing edge sector. In contrast, edges adjacent to non-cleared infestation were revealed as less attractive for subsequent infestations, but nonetheless more attractive than permanent forest edges or the stand interior. Additionally, we measured near-bark surface air temperature to determine microclimatic differences at those edge- or non-edge sites and related them to predisposition results. Finally, our study emphasized favourable microclimatic conditions—summarized as the “sun-effect”—as a decisive factor enhancing the local infestation probability at recent forest edges in multiple ways. Both insect- and host tree-related reactions to suddenly altered microclimate are supposed to bias arbitrary colonization behaviour at patch and tree level, thereby mainly explaining observed infestation patterns. From the forester’s point of view, our results may contribute to precise bark beetle risk assessment and thus facilitate decision making in forest management.

Background Dispersal is a key process in the response of insect populations to rapidly changing environmental conditions. Variability among individuals, regarding the timing of dispersal initiation and travelled distance from source, is assumed to contribute to increased population success through risk spreading. However, experiments are often limited in studying complex dispersal interactions over space and time. By applying a local-scaled individual-based simulation model we studied dispersal and emerging infestation patterns in a host − bark beetle system (Picea abies – Ips typgraphus). More specifically, we (i) investigated the effect of individual variability in beetle physiology (flight capacity) and environmental heterogeneity (host susceptibility level) on population-level dispersal success, and (ii) elucidated patterns of spatial and/or temporal variability in individual dispersal success, host selectivity, and the resulting beetle density within colonized hosts in differently susceptible environments. Results Individual variability in flight capacity of bark beetles causes predominantly positive effects on population-level dispersal success, yet these effects are strongly environment-dependent: Variability is most beneficial in purely resistant habitats, while positive effects are less pronounced in purely susceptible habitats, and largely absent in habitats where host susceptibility is spatially scattered. Despite success rates being highest in purely susceptible habitats, scattered host susceptibility appeared most suitable for dispersing bark beetle populations as it ensures population spread without drastically reducing success rates. At the individual level, dispersal success generally decreases with distance to source and is lowest in early flight cohorts, while host selectivity increased and colonization density decreased with increasing distance across all environments. Conclusions Our modelling approach is demonstrated to be a powerful tool for studying movement ecology in bark beetles. Dispersal variability largely contributes to risk spreading among individuals, and facilitates the response of populations to changing environmental conditions. Higher mortality risk suffered by a small part of the dispersing population (long-distance dispersers, pioneers) is likely paid off by reduced deferred costs resulting in fitness benefits for subsequent generations. Both, dispersal variability in space and time, and environmental heterogeneity are characterized as key features which require particular emphasis when investigating dispersal and infestation patterns in tree-killing bark beetles. Electronic supplementary material The online version of this article (doi:10.1186/s40462-016-0074-9) contains supplementary material, which is available to authorized users.

Plantations released from management are vulnerable to transient oscillations until cohort dynamics are broken and the vertical and horizontal structures of the plantation are transformed to those of more natural forests. Cohort-desynchronizing factors such as canopy disturbances are expected to accelerate this process. Using well-established mangrove plantations in Can Gio (Viet Nam) as an example, we tested whether lightning gaps can affect transition dynamics of plantations to more natural forests by damping the amplitude or by shortening the period of oscillations in tree densities. This was done by applying point pattern analyses to remotely sensed data, and by further combining statistical and individual-based modelling. The occurrence of lightning gaps was biased by the forest matrix, which presented a challenge for the point pattern analysis. This problem was solved by using the scattered forest area as a binary mask. A Matern cluster process model was found to be suitable for describing the lightning regime. This statistical model was incorporated into the individual-based mangrove model KiWi, and simulation experiments revealed that: (i) the evenly spaced distribution of the tree cohorts in the plantation supports non-linear transition behaviour, i.e. oscillation of tree density, and (ii) the lightning regime in Can Gio damps the oscillation amplitude but is not sufficient to prevent the latter nor to decrease the length of the period of oscillations.

Spatio-temporal dispersal of pest species such as bark beetles plays a key role in their population ecology and outbreak dynamics. Understanding the underlying patterns is crucial for applying appropriate management strategies. In contrast to most existing studies which focus on dispersing beetles, we analysed patches of killed trees resulting from bark beetle infestation. The study was based on a 22-year time series of annually captured colour-infrared (CIR) images of the Bavarian Forest National Park (Germany), where Ips typographus L. (Coleoptera, Curculionidae, Scolytinae) propagates undisturbed by human activity. Newly infested patches comprising at least 5 spruce trees were identified in every time step. This investigation of spatio-temporal spread of infestations primarily focused on (i) parameterizing the size and shape of infestation patches, (ii) modelling an infestation gradient and (iii) evaluating the risk of subsequent infestations on landscape scale. We developed a GIS-based distance ring approach to quantify the distance relation of subsequent infestations, including the distribution of potential hosts. Infestation spread was revealed to be strongly distance dependent, following an inverse power law function: on average 65% of new infestations occurred within a 100 m radius of the previous year’s infestations, and 95% within 500 m. ‘Distance’ proved to be a major determinant of I. typographus dispersal on the landscape scale in each time step of the 22-year series we investigated. Infestation distance thus describes the outcome of beetle dispersal very accurately. The time series showed two alternating periods of epidemic and non-epidemic infestation. These gradation stages did not affect the size and shape of infested patches, but epidemics correlated significantly with a higher percentage of infestations within short distances. Additionally, the resulting infestation risk is highly sensitive to the gradation stage, particularly within the first 100 m around source spots where it increases up to 30%. Our study therefore contributes to a better understanding of the outbreak dynamics of I. typographus and suggests concentrating efficient bark beetle management on areas in the close vicinity of previous years’ infestations.

Governments worldwide engage in open government initiatives for making their data and related information available to the public. But the success of open government is contingent upon the public's willingness to use and exploit these data sets. Governments need to have a clear understanding of the factors impacting users' intentions to make use of their open government offerings. In this paper, we answer the following research question: What factors influence the intention to use open government services and offerings? We empirically analyze an online survey, which was administered in six countries in 2013 with over 6.000 valid responses. Our research model builds on TAM and UTAUT. The results of our analysis indicate that perceived advantage, perceived ease of use, geographical closeness of topic and political activity directly influence the intention to use open government. Trust of Internet and perceived risks appear to have no direct impact on open government usage.

Biological infestations in forests, e.g. the insect outbreaks, have been shown as favoured by future climate change trends. In Europe, the European spruce bark beetle (Ips typographus L.) is one of the main agents causing substantial economic disturbances in forests. Therefore, studies on spatio-temporal characterization of the area affected by bark beetle are of major importance for rapid post-attack management. We aimed at spatially detecting damage classes by combining multidate remote sensing data and a non-parametric classification. As study site served a part of the Bavarian Forest National Park (Germany). For the analysis, we used 10 geometrically rectified scenes of Landsat and SPOT sensors in the period between 2001 and 2011. The main objective was to explore the potential of medium-resolution data for classifying the attacked areas. A further aim was to explore if the temporally adjacent infested areas are able to be separated. The random forest (RF) model was applied using the reference data drawn from high-resolution aerial imagery. The results indicate that the sufficiently large patches of visually identifiable damage classes can be accurately separated from non-attacked areas. In contrast to those, the other mortality classes (current year, current year 1 and current year 2 infested classes) were mostly classified with higher commission or omission errors as well as higher classification biases. The available medium-resolution satellite images, combined with properly acquired reference data, are concluded to be adequate tools to map area-based infestations at advanced stages. However, the quality of reference data, the size of infested patches and the spectral resolution of remotely sensed data are the decisive factors in case of smaller areas. Further attempts using auxiliary height information and spatially enhanced data may refine such an approach.

A large spatio-temporal data set monitoring the annual progress of bark beetle infestation in the Bavarian Forest National Park (Germany) is statistically analysed by means of complex image analysis algorithms. The infestation data were obtained by color-infrared (CIR) aerial image interpretation and cover 10 subsequent years (2001–2010). Newly emerged infestation patches are hypothesized as spatially correlated to locations of previous year’s infestation. Both areas, source patches and subsequently emerged patches, are considered as two disjoint random sets. Their spatio-temporal dependence is analysed by two methods: the classical approach based on the measurement of cross-covariance functions, and a second one based on nearest neighbor distances. The resulting characteristics can be interpreted as pre-disposition probabilities of bark beetle infestation depending on distance to sources. Both methods show a strong short-range preference, which decreases with increasing distances.

44 pages, 9 tables, 9 figures.-- Corinne Le Quéré ... et al.-- This work is distributed under the Creative Commons Attribution 4.0 License, Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere – the "global carbon budget" – is important to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe data sets and methodology to quantify the five major components of the global carbon budget and their uncertainties. CO2 emissions from fossil fuels and industry (EFF) are based on energy statistics and cement production data, respectively, while emissions from land-use change (ELUC), mainly deforestation, are based on land-cover change data and bookkeeping models. The global atmospheric CO2 concentration is measured directly and its rate of growth (GATM) is computed from the annual changes in concentration. The ocean CO2 sink (SOCEAN) and terrestrial CO2 sink (SLAND) are estimated with global process models constrained by observations. The resulting carbon budget imbalance (BIM), the difference between the estimated total emissions and the estimated changes in the atmosphere, ocean, and terrestrial biosphere, is a measure of imperfect data and understanding of the contemporary carbon cycle. All uncertainties are reported as ±1σ. For the last decade available (2007–2016), EFF was 9.4 ± 0.5 GtC yr−1, ELUC 1.3 ± 0.7 GtC yr−1, GATM 4.7 ± 0.1 GtC yr−1, SOCEAN 2.4 ± 0.5 GtC yr−1, and SLAND 3.0 ± 0.8 GtC yr−1, with a budget imbalance BIM of 0.6 GtC yr−1 indicating overestimated emissions and/or underestimated sinks. For year 2016 alone, the growth in EFF was approximately zero and emissions remained at 9.9 ± 0.5 GtC yr−1. Also for 2016, ELUC was 1.3 ± 0.7 GtC yr−1, GATM was 6.1 ± 0.2 GtC yr−1, SOCEAN was 2.6 ± 0.5 GtC yr−1, and SLAND was 2.7 ± 1.0 GtC yr−1, with a small BIM of −0.3 GtC. GATM continued to be higher in 2016 compared to the past decade (2007–2016), reflecting in part the high fossil emissions and the small SLAND consistent with El Niño conditions. The global atmospheric CO2 concentration reached 402.8 ± 0.1 ppm averaged over 2016. For 2017, preliminary data for the first 6–9 months indicate a renewed growth in EFF of +2.0 % (range of 0.8 to 3.0 %) based on national emissions projections for China, USA, and India, and projections of gross domestic product (GDP) corrected for recent changes in the carbon intensity of the economy for the rest of the world. This living data update documents changes in the methods and data sets used in this new global carbon budget compared with previous publications of this data set (Le Quéré et al., 2016, 2015b, a, 2014, 2013). All results presented here can be downloaded from https://doi.org/10.18160/GCP-2017 (GCP, 2017)