Consistent, large-scale operational monitoring of forest height is essential for estimating forest-related carbon emissions, analyzing forest degradation, and quantifying the effectiveness of forest ...restoration initiatives. The Global Ecosystem Dynamics Investigation (GEDI) lidar instrument onboard the International Space Station has been collecting unique data on vegetation structure since April 2019. Here, we employed global Landsat analysis-ready data to extrapolate GEDI footprint-level forest canopy height measurements, creating a 30 m spatial resolution global forest canopy height map for the year 2019. The global forest height map was compared to the GEDI validation data (RMSE = 6.6 m; MAE = 4.45 m, R2 = 0.62) and available airborne lidar data (RMSE = 9.07 m; MAE = 6.36 m, R2 = 0.61). The demonstrated integration of GEDI data with time-series optical imagery is expected to enable multidecadal historic analysis and operational forward monitoring of forest height and its dynamics. Such capability is important to support global climate and sustainable development initiatives.
Aim
Climate‐induced range expansion ultimately implies recruitment at sites that were previously unoccupied by a species (i.e. colonization events). Using evidence on abiotic conditions and biotic ...interactions at these migration sites, we aimed to identify migration pathways from northern temperate to boreal forests for species showing northward range expansion.
Location
Quebec, Canada.
Taxon
Trees of northern temperate/boreal forests.
Methods
Using past (1970–1977) and recently updated (2003–2015) forest inventories across 761,100 km2, we first quantified latitudinal shifts for saplings of eight tree species and investigated colonization events at migration sites. We used field evidence and a consensus modelling approach to determine environmental suitability and identify edaphic, climatic and disturbance conditions, as well as species co‐occurrence patterns, characterizing recent colonization events. The results were interpreted in relation to novel species associations facilitating species migration in unsuitable landscapes.
Results
All species showed northward latitudinal shifts driven by increased recruitment and colonization northward. Colonization events occurred largely at historically unsuitable sites. Migration sites showed a shift towards humus types characteristic of the boreal forest and not typically found in the core range of most temperate species. Climatic conditions at migration sites were initially colder than at occupied sites, but warming suggests recent climatic suitability. A decrease in conifer basal area at migration sites following disturbances reduced priority effects that possibly constrained deciduous species establishment. Co‐occurrence patterns pointed to deciduous species tolerant of boreal edaphic conditions, leading the way for other temperate species.
Main conclusions
Temperate tree species can recruit into sites typical of boreal forests, even under environmentally challenging conditions. Warming and disturbances open up the way for some novel species associations that in turn have the potential to facilitate the recruitment of temperate species into the boreal forest, revealing migration pathways.
Air pollution and atmospheric deposition have adverse effects on tree and forest health. We reviewed studies on tree and forest decline in Northeast and Southeast Asia, Siberia, and the Russian Far ...East (hereafter referred to as East Asia). This included studies published in domestic journals and languages. We identified information about the locations, causes, periods, and tree species exhibiting decline. Past air pollution was also reviewed. Most East Asian countries show declining trends in SO2 concentration in recent years, although Mongolia and Russia show increasing trends. Ozone (O3) concentrations are stable or gradually increasing in the East Asia region, with high maxima. Wet nitrogen (N) deposition was high in China and tropical countries, but low in Russia. The decline of trees and forests primarily occurred in the mid-latitudes of Japan, Korea, China, and Russia. Long-term large N deposition resulted in the N saturation phenomenon in Japan and China, but no clear forest health response was observed. Thereafter, forest decline symptoms, suspected to be caused by O3, were observed in Japan and China. In East Russia, tree decline occurred around industrial centers in Siberia. Haze events have been increasing in tropical and boreal forests, and particulate matter inhibits photosynthesis. In recent years, chronically high O3 concentrations, in conjunction with climate change, are likely have adverse effects on tree physiology. The effects of air pollution and related factors on tree decline are summarized. Recently, the effects of air pollution on tree decline have not been apparent under the changing climate, however, monitoring air pollution is indispensable for identifying the cause of tree decline. Further economic growth is projected in Southeast Asia and therefore, the monitoring network should be expanded to tropical and boreal forest zones. Countermeasures such as restoring urban trees and rural forests are important for ensuring future ecosystem services.
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•Tree and forest declines have followed industrialization in each country.•The causes of tree and forest decline have changed, depending on the time period.•Recent chronic effects of ozone and changing climate deteriorate tree health.•The apparent effect of air pollution was not found in recent tree decline.•An outline of future monitoring and countermeasures is proposed.
Most years in the period from 2018 to 2022 have been exceptionally dry in Central Europe. In Germany’s forests, this long-lasting drought has caused unprecedented tree mortality. Systematic ...ground-based surveys, such as the annual Crown Condition Survey, provide information on the vitality status of the different tree species and their mortality rates. However, models are needed to be able to map the spatial patterns of mortality for each tree species based on cause-effect relationships derived from field observations. In this study, logistic regression models were used to identify the most important drivers of mortality for the most important tree species in Germany. For this purpose, the dead and surviving trees from the Crown Condition Survey were combined with a large set of potential predictor variables from the domains of climate, topography, soil, land cover and deposition. After feature selection, the models were evaluated using the area under the curve (AUC) statistic. Norway spruce (Picea abies; AUC = 0.9) showed by far the greatest increase in mortality, with the country-wide average observed and predicted rates approaching almost 10% per year from 2020 to 2022, and much higher predicted rates at the regional level. Much of the spruce mortality was explained by the climatic water balance of the driest summer in previous years. The other main tree species also showed clear mortality responses to the drought conditions. However, in the case of European beech (Fagus sylvatica; AUC = 0.94) and Pedunculate and Sessile oak (Quercus robur and petraea; AUC = 0.88), the peaks in the time series of the country-wide mortality rates stayed below 1%. For these broadleaved species, mortality was more dependent on a range of site conditions, i.e., soil and topography. For Scots pine (Pinus sylvestris; AUC = 0.76), for which the observed mortality rate peaked at 1.2% in 2020, the given drivers could explain mortality only to a lesser degree than for the other species. The regression models were used for spatial prediction to produce country-wide maps of species-specific mortality rates at annual temporal and 100-m spatial resolution, covering all years from 1998 to 2022. The maps visualize the spatial patterns of mortality over time. The regions in western and central Germany, which were most seriously affected by spruce dieback can clearly be identified. The models and maps presented can be used for risk assessment, forest planning, and tree species selection, providing decision support for forest practitioners.
•Logistic regression models for predicting tree mortality.•Maps showing regions of high mortality in Germany for the years 1998–2022.•Drought from 2018 to 2022 impacted all main species, but to a varying degree.•High prediction accuracies for Norway spruce, European beech and oak species.•Importance rankings of the main environmental drivers of mortality.
The objectives of this study were to estimate above ground forest biomass and identify areas disturbed by selective logging in a 1000ha Brazilian tropical forest in the Antimary State Forest (FEA) ...using airborne lidar data. The study area consisted of three management units, two of which were unlogged, while the third unit was selectively logged at a low intensity (approximately 10–15m3 ha−1 or 5–8% of total volume). A systematic random sample of fifty 0.25-ha ground plots were measured and used to construct lidar-based regression models for above ground biomass (AGB). A lidar model-assisted approach was used to estimate AGB for the logged and unlogged units (using both synthetic and model-assisted estimators). Two lidar explanatory variables, computed at a spatial resolution of 50m×50m, were used in these predictions: 1) the first quartile height of all above ground returns (P25); and, 2) variance of the height above ground of all returns (VAR). The model-assisted AGB estimator (total 231,589Mg±5,477 SE; mean 231.6Mg ha−1±5.5 SE; ±2.4%) was more precise than plot-only simple random sample estimator (total 230,872Mg±10,477 SE; mean 230.9Mg ha−1±10.5 SE; ±4.5%). The total and mean AGB estimates obtained using the synthetic estimator (total 231,694Mg; mean 231.7Mg ha−1) were nearly equal those obtained using the model-assisted estimator. In a second component of the analysis lidar metrics were also computed at 1m×1m resolution to identify areas impacted by logging activities within the selectively harvested management unit. A high-resolution canopy relative density model (RDM) was used in GIS to identify and delineate roads, skidtrails, landings and harvested tree gaps. The area impacted by selective logging determined from the RDM was 58.4ha or 15.4% of the total management unit. Using these two spatial resolutions of lidar analyses it was possible to identify differences in AGB in selectively logged areas that had relatively high levels of residual overstory canopy cover. The mean AGB obtained from the synthetic estimator was significantly lower in impacted areas than in undisturbed areas of the selectively logged management unit (p=0.01).
► Lidar was used to improve estimates of biomass in a managed Amazon forest. ► Selective logging in a managed Amazon forest was successfully mapped with lidar data. ► Lidar can be used to monitor low-intensity, selective logging in tropical forests.
Average nitrogen (N) deposition across Europe has declined since the 1990s. This resulted in decreased N inputs to forest ecosystems especially in Central and Western Europe where deposition levels ...are highest. While the impact of atmospheric N deposition on forests has been receiving much attention for decades, ecosystem responses to the decline in N inputs received less attention. Here, we review observational studies reporting on trends in a number of indicators: soil acidification and eutrophication, understory vegetation, tree nutrition (foliar element concentrations) as well as tree vitality and growth in response to decreasing N deposition across Europe. Ecosystem responses varied with limited decrease in soil solution nitrate concentrations and potentially also foliar N concentrations. There was no large-scale response in understory vegetation, tree growth, or vitality. Experimental studies support the observation of a more distinct reaction of soil solution and foliar element concentrations to changes in N supply compared to the three other parameters. According to the most likely scenarios, further decrease of N deposition will be limited. We hypothesize that this expected decline will not cause major responses of the parameters analysed in this study. Instead, future changes might be more strongly controlled by the development of N pools accumulated within forest soils, affected by climate change and forest management.
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•Europe's forests show limited response to decreasing N deposition.•Potential responses have been reported for soil solution and foliage concentrations.•Delayed or marginal responses are expected for other forest ecosystem components.•Future decrease of N deposition to forests in Europe will likely be small.
We find limited indication for response of Europe's forests to declining N deposition. Reactions have been reported for soil solution NO3− and potentially foliar N concentrations but not for other indicators.
Forests are increasingly affected by global change. Building resilient forests requires – amongst others - leveraging the wealth of knowledge from existing ground-based, field inventory and ...monitoring programs as well as Earth Observation systems to better assess the status, detect changes, understand processes, predict future dynamics, and guide forest management. A proposal from the European Commission for a new forest monitoring framework at the European level aims in this direction but lacks the integration of some crucial and readily available resources and infrastructures. For this reason, the proposal risks to be a missed opportunity rather than a step forward. Here we provide suggestions to help reconciling the proposal with its objectives and a more comprehensive monitoring vision.
•“Resilient forests” requires monitoring to better understand their functioning.•The EC forest monitoring proposal lacks this aspect and ignore existing resources.•Jointing monitoring forces is necessary for a better international forest monitoring
•A UNet type convolutional neural network is used to estimate vegetation height from Sentinel2-data.•The method achieves a mean average error (MAE) of 4.6 m.•A change detection scheme is proposed to ...detect clear cutting events in vegetation height time series.
We propose and investigate a method for creating large scale forest height maps at 10 m resolution from Sentinel-2 data using deep neural networks. In addition, we demonstrate how clear-cutting events can be detected in a time series of the resulting forest height maps. The network architecture is a convolutional neural network based on the U-Net architecture. The 13 Sentinel-2 spectral bands are resampled to 10 m spatial resolution and input to the U-Net, which outputs a map with per-pixel forest height estimates. The network is trained with ground truth data acquired from airborne lidar scanning surveys from three different geographical regions. They cover different types of forests: lowland tropical rainforest in the Democratic Republic of Congo, Miombo woodlands (dry forest) in Liwale, Tanzania, and submontane tropical rainforest in Amani, Tanzania. We demonstrate that the trained network generalizes to new geographical regions within the African continent with a mean average error of 4.6 m. This is on-par with a previously published method’s ability to generalize to new geographical regions within the same country. Clear-cutting events are detected using a t-test. The null-hypothesis of the t-test is that the forest height has not changed after any given point in time in the forest height time-series.
European standards for the protection of forests from ozone (O3) are based on atmospheric exposure (AOT40) that is not always representative of O3 effects since it is not a proxy of gas uptake ...through stomata (stomatal flux). MOTTLES “MOnitoring ozone injury for seTTing new critical LEvelS” is a LIFE project aimed at establishing a permanent network of forest sites based on active O3 monitoring at remote areas at high and medium risk of O3 injury, in order to define new standards based on stomatal flux, i.e. PODY (Phytotoxic Ozone Dose above a threshold Y of uptake). Based on the first year of data collected at MOTTLES sites, we describe the MOTTLES monitoring station, together with protocols and metric calculation methods. AOT40 and PODY, computed with different methods, are then compared and correlated with forest–health indicators (radial growth, crown defoliation, visible foliar O3 injury). For the year 2017, the average AOT40 calculated according to the European Directive was even 5 times (on average 1.7 times) the European legislative standard for the protection of forests. When the metrics were calculated according to the European protocols (EU Directive 2008/50/EC or Modelling and Mapping Manual LTRAP Convention), the values were well correlated to those obtained on the basis of the real duration of the growing season (i.e. MOTTLES method) and were thus representative of the actual exposure/flux. AOT40 showed opposite direction relative to PODY. Visible foliar O3 injury appeared as the best forest–health indicator for O3 under field conditions and was more frequently detected at forest edge than inside the forest. The present work may help the set–up of further long–term forest monitoring sites dedicated to O3 assessment in forests, especially because flux-based assessments are recommended as part of monitoring air pollution impacts on ecosystems in the revised EU National Emissions Ceilings Directive.
•The MOTTLES network for active O3 monitoring in forests is described.•In 2017, AOT40 exceeded twice the limit of the European Directive for forests.•O3 metrics from European protocols were representative of actual exposure/fluxes.•AOT40 and PODy were inversely correlated.•Visible foliar injury was the best forest–health indicator for O3.
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