Pulses of tree mortality caused by drought have been reported recently in forests around the globe, but large-scale quantitative evidence is lacking for Europe. Analyzing high-resolution annual ...satellite-based canopy mortality maps from 1987 to 2016 we here show that excess forest mortality (i.e., canopy mortality exceeding the long-term mortality trend) is significantly related to drought across continental Europe. The relationship between water availability and mortality showed threshold behavior, with excess mortality increasing steeply when the integrated climatic water balance from March to July fell below -1.6 standard deviations of its long-term average. For -3.0 standard deviations the probability of excess canopy mortality was 91.6% (83.8-97.5%). Overall, drought caused approximately 500,000 ha of excess forest mortality between 1987 and 2016 in Europe. We here provide evidence that drought is an important driver of tree mortality at the continental scale, and suggest that a future increase in drought could trigger widespread tree mortality in Europe.
Natural disturbance regimes are changing substantially in forests around the globe. However, large‐scale disturbance change is modulated by a considerable spatiotemporal variation within biomes. This ...variation remains incompletely understood particularly in the temperate forests of Europe, for which consistent large‐scale disturbance information is lacking. Here, our aim was to quantify the spatiotemporal patterns of forest disturbances across temperate forest landscapes in Europe using remote sensing data and determine their underlying drivers. Specifically, we tested two hypotheses: (1) Topography determines the spatial patterns of disturbance, and (2) climatic extremes synchronize natural disturbances across the biome. We used novel Landsat‐based maps of forest disturbances 1986–2016 in combination with landscape analysis to compare spatial disturbance patterns across five unmanaged forest landscapes with varying topographic complexity. Furthermore, we analyzed annual estimates of disturbances for synchronies and tested the influence of climatic extremes on temporal disturbance patterns. Spatial variation in disturbance patterns was substantial across temperate forest landscapes. With increasing topographic complexity, natural disturbance patches were smaller, more complex in shape, more dispersed, and affected a smaller portion of the landscape. Temporal disturbance patterns, however, were strongly synchronized across all landscapes, with three distinct waves of high disturbance activity between 1986 and 2016. All three waves followed years of pronounced drought and high peak wind speeds. Natural disturbances in temperate forest landscapes of Europe are thus spatially diverse but temporally synchronized. We conclude that the ecological effect of natural disturbances (i.e., whether they are homogenizing a landscape or increasing its heterogeneity) is strongly determined by the topographic template. Furthermore, as the strong biome‐wide synchronization of disturbances was closely linked to climatic extremes, large‐scale disturbance episodes are likely in Europe's temperate forests under climate changes.
Natural disturbance regimes are changing around the globe. Yet, we lack a comprehensive understanding of the spatiotemporal patterns of change. Our aim was to quantify spatiotemporal patterns of forest disturbances across the temperate forest of Europe by combining remote sensing and topographic/meteorological data. Our results show that natural disturbances in the temperate forest of Europe are spatially diverse but temporally synchronized. We conclude that the ecological effects of natural disturbances are strongly determined by the topographic template, and that synchronization of disturbance activity is linked to climatic extremes. Large‐scale disturbance episodes are hence likely in Europe under climate change.
Abstract Canopy openings are increasing in Europe’s forests, yet the contributions of anthropogenic and ecological agents of disturbance to this increase remain debated. Here we attribute the root ...cause of all stand-replacing canopy disturbances identified for Europe in the period 1986–2020 from Landsat data (417,000 km²), distinguishing between planned and unplanned canopy openings (i.e., disturbance by human land use versus by wind, bark beetles, and wildfire). We show that canopy openings by humans dominate the European forest disturbance regime, accounting for 82% of the area disturbed. Both planned and unplanned canopy openings increased in the early 21st century (+24% and +30% relative to the late 20th century). Their changes are linked, with simultaneous increases in planned and unplanned canopy openings on 68% of Europe’s forest area. We conclude that an important direction for tackling disturbance change in policy and management is to break the link between planned and unplanned canopy openings in Europe’s forests.
•Annual start of season estimates from combined Landsat and Sentinel-2 time series.•Choice of vegetation index more important than choice of model.•Results indicate higher suitability of EVI for ...estimating start of season than NDVI.•Combination of sensors improved estimates compared to single-sensor time series.•Decreasing observation frequency diminished start of season estimates.
Vegetation phenology has a great impact on land-atmosphere interactions like carbon cycling, albedo, and water and energy exchanges. To understand and predict these critical land-atmosphere feedbacks, it is crucial to measure and quantify phenological responses to climate variability, and ultimately climate change. Coarse-resolution sensors such as MODIS and AVHRR have been useful to study vegetation phenology from regional to global scales. These sensors are, however, not capable of discerning phenological variation at moderate spatial scales. By offering increased observation density and higher spatial resolution, the combination of Landsat and Sentinel-2 time series might provide the opportunity to overcome this limitation.
In this study, we analyzed the potential of combined Sentinel-2 and Landsat time series for estimating start of season (SOS) of broadleaf forests across Germany for the year 2018. We tested two common statistical modeling approaches (logistic and generalized additive models using thin plate splines) and the two most commonly used vegetation indices, the Normalized Difference Vegetation Index (NDVI) and the Enhanced Vegetation Index (EVI).
We found strong agreement between SOS estimates from logistic and spline models (rEVI = 0.86; rNDVI = 0.65), whereas agreement was higher for EVI than for NDVI (RMSDEVI = 3.07, RMSDNDVI = 5.26 days). The choice of vegetation index thus had a higher impact on the results than the fitting method. The EVI-based SOS also showed higher correlation with ground observations compared to NDVI (rEVI = 0.51, rNDVI = 0.42). Data density played an important role in estimating land surface phenology. Models combining Sentinel-2A/B, with an average cloud-free observation frequency of 12 days, were largely consistent with the combined Landsat and Sentinel-2 models, suggesting that Sentinel-2A/B may be sufficient to capture SOS for most areas in Germany in 2018. However, in non-overlapping swath areas and mountain areas, observation frequency was significantly lower, underlining the need to combine Landsat and Sentinel-2 for consistent SOS estimates over large areas. Our study demonstrates that estimating SOS of temperate broadleaf forests at medium spatial resolution has become feasible with combined Landsat and Sentinel-2 time series.
Mortality is a key indicator of forest health, and increasing mortality can serve as bellwether for the impacts of global change on forest ecosystems. Here we analyze trends in forest canopy ...mortality between 1984 and 2016 over more than 30 Mill. ha of temperate forests in Europe, based on a unique dataset of 24,000 visually interpreted spectral trajectories from the Landsat archive. On average, 0.79% of the forest area was affected by natural or human-induced mortality annually. Canopy mortality increased by +2.40% year
, doubling the forest area affected by mortality since 1984. Areas experiencing low-severity mortality increased more strongly than areas affected by stand-replacing mortality events. Changes in climate and land-use are likely causes of large-scale forest mortality increase. Our findings reveal profound changes in recent forest dynamics with important implications for carbon storage and biodiversity conservation, highlighting the importance of improved monitoring of forest mortality.
Disturbance regimes are changing in forests across the world in response to global climate change. Despite the profound impacts of disturbances on ecosystem services and biodiversity, assessments of ...disturbances at the global scale remain scarce. Here, we analyzed natural disturbances in boreal and temperate forest ecosystems for the period 2001–2014, aiming to 1) quantify their within‐ and between‐biome variation and 2) compare the climate sensitivity of disturbances across biomes. We studied 103 unmanaged forest landscapes with a total land area of 28.2 × 106 ha, distributed across five continents. A consistent and comprehensive quantification of disturbances was derived by combining satellite‐based disturbance maps with local expert knowledge of disturbance agents. We used Gaussian finite mixture models to identify clusters of landscapes with similar disturbance activity as indicated by the percent forest area disturbed as well as the size, edge density and perimeter–area‐ratio of disturbed patches. The climate sensitivity of disturbances was analyzed using Bayesian generalized linear mixed effect models and a globally consistent climate dataset. Within‐biome variation in natural disturbances was high in both boreal and temperate biomes, and disturbance patterns did not vary systematically with latitude or biome. The emergent clusters of disturbance activity in the boreal zone were similar to those in the temperate zone, but boreal landscapes were more likely to experience high disturbance activity than their temperate counterparts. Across both biomes high disturbance activity was particularly associated with wildfire, and was consistently linked to years with warmer and drier than average conditions. Natural disturbances are a key driver of variability in boreal and temperate forest ecosystems, with high similarity in the disturbance patterns between both biomes. The universally high climate sensitivity of disturbances across boreal and temperate ecosystems indicates that future climate change could substantially increase disturbance activity.
Defoliators and bark beetles are natural disturbance agents in many forest ecosystems around the world. Mapping the spatial and temporal patterns of insect disturbance dynamics can help in ...understanding their impacts on forest ecosystem resilience and functioning, and in developing adaptive management strategies. In recent years, much progress has been made in landscape-level analyses of insect-induced disturbances using remotely sensed data. However, many studies have focused on single insect agents or aggregated different insect agents into a single group. In this study, we characterized the temporal-spectral patterns associated with bark beetle and defoliator disturbances using Landsat time series between 1990 and 2013, with the objective to test if the two insect disturbances can be separated with Landsat data. We analyzed a recent outbreak of mountain pine beetle (Dendroctonus ponderosae Hopkins) and western spruce budworm (Choristoneura freemani Razowski) in British Columbia, Canada. To characterize the disturbance and recovery trends associated with insect disturbances we used the LandTrendr segmentation algorithm. We fitted LandTrendr spectral trajectories to annual normalized burn ratio (NBR) and Tasseled Cap (TC) time series, from which we then extracted a set of disturbance metrics. With these disturbance metrics, two random forest models were trained to a) distinguish insect disturbances from harvest and fire disturbances; and to b) attribute the insect disturbances to the most likely agent, i.e. mountain pine beetle or western spruce budworm. Insect disturbances were successfully mapped with an overall accuracy of 76.8%, and agents were successfully attributed with overall accuracies ranging from 75.3% to 88.0%, depending on whether only pure host-stands or mixed stands with both insect hosts were considered. In the case of mixed host stands, nearly 45% of the western spruce budworm disturbances were falsely attributed to mountain pine beetle. Spectral metrics describing disturbance magnitude were more important for distinguishing the two insect agents than the disturbance duration. Spectral changes associated with western spruce budworm disturbances had generally lower magnitudes than mountain pine beetle disturbances. Moreover, disturbances by western spruce budworm were more strongly associated with changes in TC greenness, whereas disturbances by mountain pine beetle were more strongly associated with changes in TC brightness and wetness. The results reflect the ephemeral nature of defoliators versus the tree mortality impacts of bark beetles in our study area. This study demonstrates the potential of Landsat time series for mapping bark beetle and defoliator disturbances at the agent level and highlights the need for distinguishing between the two insect agents to adequately capture their impacts on ecosystem processes.
•Defoliator and bark beetle disturbances were separated with Landsat time series.•Separability decreased in stands where hosts of both agents were present.•Disturbance magnitude and duration were both important for separation.•Defoliators caused changes in TC Greenness, likely associated with loss in foliage.•Bark beetles caused changes in TC Wetness, likely associated with tree mortality.
River water quality monitoring at limited temporal resolution can lead to imprecise and inaccurate classification of physicochemical status due to sampling error. Bayesian inference allows for the ...quantification of this uncertainty, which can assist decision-making. However, implicit assumptions of Bayesian methods can cause further uncertainty in the uncertainty quantification, so-called second-order uncertainty. In this study, and for the first time, we rigorously assessed this second-order uncertainty for inference of common water quality statistics (mean and 95th percentile) based on sub-sampling high-frequency (hourly) total reactive phosphorus (TRP) concentration data from three watersheds. The statistics were inferred with the low-resolution sub-samples using the Bayesian lognormal distribution and bootstrap, frequentist
t
test, and face-value approach and were compared with those of the high-frequency data as benchmarks. The
t
test exhibited a high risk of bias in estimating the water quality statistics of interest and corresponding physicochemical status (up to 99% of sub-samples). The Bayesian lognormal model provided a good fit to the high-frequency TRP concentration data and the least biased classification of physicochemical status (< 5% of sub-samples). Our results suggest wide applicability of Bayesian inference for water quality status classification, a new approach for regulatory practice that provides uncertainty information about water quality monitoring and regulatory classification with reduced bias compared to frequentist approaches. Furthermore, the study elucidates sizeable second-order uncertainty due to the choice of statistical model, which could be quantified based on the high-frequency data.
Context
Structural diversity strongly influences habitat quality and the functioning of forest ecosystems. An important driver of the variation in forest structures are disturbances. As disturbances ...are increasing in many forest ecosystems around the globe, it is important to understand how structural diversity responds to (changing) disturbances.
Objectives
Our aim was to quantify the relationship between forest disturbances and structural diversity with a focus on diversity in canopy height.
Methods
We assessed diversity in canopy height for two strictly protected Central European forest landscapes using lidar data. We used a multi-scale framework to quantify within-patch (α), between-patch (β), and overall (γ) diversity. We then analysed the variation in canopy height diversity over an extensive gradient of disturbance rates.
Results
Diversity in canopy height was strongly driven by disturbance rate, with highest overall diversity between 0.5 and 1.5% of the forest area disturbed per year. The unimodal responses of overall diversity to disturbance emerged from contrasting within- and between-patch responses, i.e., a decrease in within-patch diversity and an increase in between-patch diversity with increasing disturbance. This relationship was consistent across study landscapes, spatial scales, and diversity indicators.
Conclusion
The recent wave of natural disturbances in Central Europe has likely fostered the structural diversity of forest landscapes. However, a further increase in disturbance could result in the crossing of a tipping point (at ~ 1.5% of forest area disturbed per year), leading to substantial structural homogenization.
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