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Mediterranean forest ecosystems are highly vulnerable to climate extremes and anomalies induced by climate change, as evidenced by the increase in forest tree decline and death over the past few decades. Forest dieback may occur with different spatial patterns and in response to many climatic and weather events (i.e., drought spells, heat waves, compound events or hot drought, cold spells, and windstorms). This paper describes the physiological behaviour of Mediterranean tree species (namely evergreen sclerophyllous trees) under extreme climatic events, with a focus on embolism formation and carbon depletion. Additionally, we describe three widely recognised patterns of forest dieback: die-off, patchy dieback, and salt and pepper dieback. Overall, drought spells, heat waves, and compound events have been reported to induce all the mortality patterns described, revealing the great vulnerability of Mediterranean forests to rising air temperature and vapour pressure deficit trends. Many intrinsic factors of plant and structural and contingent factors of the forest can interact, favouring one mortality pattern over another. Patterns of dieback and mortality are the product of the interaction between the complexity of the landscape, the species assemblage, the kind and intensity of the disturbance, and biotic factors. Different patterns have different ecological consequences, and implications for monitoring and management. The combination of terrestrial and remote sensing (RS) is recommended.

Background The mechanisms leading to dieback and death of trees under drought remain unclear. To gain an understanding of these mechanisms, addressing major empirical gaps regarding tree structure–function relations remains essential. Scope We give reasons to think that a central factor shaping plant form and function is selection simultaneously favouring constant leaf-specific conductance with height growth and isometric (1:1) scaling between leaf area and the volume of metabolically active sink tissues ('sapwood'). Sapwood volume–leaf area isometry implies that per-leaf area sapwood volumes become transversely narrower with height growth; we call this 'stretching'. Stretching means that selection must favour increases in permeability above and beyond that afforded by tip-to-base conduit widening ("ultra-widening permeability"), via fewer and wider vessels or tracheids with larger pits or larger margo openings. Leaf area–metabolically active sink tissue isometry would mean that it is unlikely that larger trees die during drought because of carbon starvation due to greater sink–source relationships as compared to shorter plants. Instead, an increase in permeability is most plausibly associated with greater risk of embolism, and this seems a more probable explanation of the preferential vulnerability of larger trees to climate change-induced drought. Other implications of selection favouring constant per-leaf area sapwood construction and maintenance costs are departure from the da Vinci rule expectation of similar sapwood areas across branching orders, and that extensive conduit furcation in the stem seems unlikely. Conclusions Because all these considerations impact the likelihood of vulnerability to hydraulic failure versus carbon starvation, both implicated as key suspects in forest mortality, we suggest that these predictions represent essential priorities for empirical testing. [ABSTRACT FROM AUTHOR]

Natural and anthropogenic disturbances are important drivers of tree mortality, shaping the structure, composition, and biomass distribution of forest ecosystems. Differences in disturbance regimes, characterized by the frequency, extent, and intensity of disturbance events, result in structurally different landscapes. In this study, we design a model‐based experiment to investigate the links between disturbance regimes and spatial biomass patterns. First, the effects of disturbance events on biomass patterns are simulated using a simple dynamic carbon cycle model based on different disturbance regime attributes, which are characterized via three parameters: μ (probability scale), α (clustering degree), and β (intensity slope). 856,800 dynamically stable biomass patterns were then simulated using combined disturbance regime, primary productivity, and background mortality. As independent variables, we use biomass synthesis statistics from simulated biomass patterns to retrieve three disturbance regime parameters. Results show confident inversion of all three "true" disturbance parameters, with Nash‐Sutcliffe efficiency of 94.8% for μ, 94.9% for α, and 97.1% for β. Biomass histogram statistics primarily dominate the prediction of μ and β, while texture features have a more substantial influence on α. Overall, these results demonstrate the association between biomass patterns and disturbance regimes. Given the increasing availability of Earth observation of biomass, our findings open a new avenue to understand better and parameterize disturbance regimes and their links with vegetation dynamics under climate change. Ultimately, at a large scale, this approach would improve our current understanding of controls and feedback at the biosphere‐atmosphere interface in the present Earth system models. Plain Language Summary: Forest dynamics are shaped by different disturbances, which are challenging to monitor and predict. Identifying individual disturbance occurrences and their impact on forest carbon stocks (biomass) is complex. However, our study deciphers the characteristics of disturbance occurrence, that is, disturbance regime, from biomass pattern. We characterized this regime across three dimensions: extent (μ), frequency (α), and intensity (β). Through a 200‐year landscape experiment, we explored the synthetic dynamically stable biomass under different disturbance regimes. Statistical features from biomass simulations revealed distinct spatial patterns, forming a connection between these patterns and the disturbance regime parameters via machine learning. Notably, specific biomass pattern statistics influence distinct disturbance regime parameters: μ and β are linked to histogram stats, while α is tied to texture statistics. This approach establishes a framework to diagnose disturbance regimes from biomass patterns, offering a way to incorporate these regimes into Earth system models. Key Points: We investigate the link between disturbance regimes and spatial patterns of aboveground biomass emerging from diverse primary productivityThe proposed framework allows for inferring disturbance probability, size and intensity from spatial features in aboveground biomassDisturbance regimes from high‐res Earth observations can enhance carbon cycle dynamics prediction from interannual to longer time scales [ABSTRACT FROM AUTHOR]

Abstract Natural and anthropogenic disturbances are important drivers of tree mortality, shaping the structure, composition, and biomass distribution of forest ecosystems. Differences in disturbance regimes, characterized by the frequency, extent, and intensity of disturbance events, result in structurally different landscapes. In this study, we design a model‐based experiment to investigate the links between disturbance regimes and spatial biomass patterns. First, the effects of disturbance events on biomass patterns are simulated using a simple dynamic carbon cycle model based on different disturbance regime attributes, which are characterized via three parameters: μ (probability scale), α (clustering degree), and β (intensity slope). 856,800 dynamically stable biomass patterns were then simulated using combined disturbance regime, primary productivity, and background mortality. As independent variables, we use biomass synthesis statistics from simulated biomass patterns to retrieve three disturbance regime parameters. Results show confident inversion of all three “true” disturbance parameters, with Nash‐Sutcliffe efficiency of 94.8% for μ, 94.9% for α, and 97.1% for β. Biomass histogram statistics primarily dominate the prediction of μ and β, while texture features have a more substantial influence on α. Overall, these results demonstrate the association between biomass patterns and disturbance regimes. Given the increasing availability of Earth observation of biomass, our findings open a new avenue to understand better and parameterize disturbance regimes and their links with vegetation dynamics under climate change. Ultimately, at a large scale, this approach would improve our current understanding of controls and feedback at the biosphere‐atmosphere interface in the present Earth system models.

Extreme weather episodes related to anthropogenic climate change have enhanced the frequency and magnitude of bark beetle disturbance, causing worldwide mortality of forests in the last decades. Changes in temperature and precipitation regimes are altering the relationships between host tree populations and associated bark beetle species, as these insect-host systems are highly sensitive to climate extremes. However, it is not fully understood how climate interacts with the different components of bark beetle-host systems, and thus, the existing knowledge is still insufficient to face the challenges of understanding the system response to changing environmental conditions. Here, we review the most important findings of the influence of climatic factors on the dynamics of bark beetle and host tree populations at different spatiotemporal scales. Future research should integrate how the effects of climate on individual tree responses to beetle attack scale up to outbreak patterns at regional scale. Recent advances in plant physiology, disturbance ecology, ecological niche modelling, and remote sensing can further our understanding of the risks of bark beetle disturbance in forest ecosystems under changing climate. [ABSTRACT FROM AUTHOR]

The Zagros forests in Iran are currently experiencing an exacerbation of climate-induced mortality, placing the Persian squirrel, a keystone species reliant on these ecosystems, in jeopardy. Addressing this imminent threat, our research employed a spatial prioritization methodology, integrating assessments of habitat suitability and mortality risk. Utilizing a weighted ensemble approach, incorporating the strengths of diverse models and expert rules, we discerned that approximately 62% of surveyed forests are at risk, with 7% classified as high risk and 17% as very high risk. Notably, 83% of the forests exhibited varying degrees of habitat suitability, with 11% and 12% demonstrating high and very high suitability, respectively. Employing a conservation prioritization framework, we systematically categorized habitats into priority classes, with 8%, 17%, 29%, and 46% assigned to very high, high, moderate, and low conservation priority classes, respectively. Significantly, areas classified as very high priority demand immediate restoration efforts due to ongoing mortality, while other priority classes underscore the importance of protection and prevention in unaffected habitats. Acknowledging the irreversible nature of current climatic conditions in the Zagros forests, our strategic emphasis aligns with conservation triage principles, prioritizing the preservation of intact habitats yet to succumb to irreversible mortality. [ABSTRACT FROM AUTHOR]

Ghost forests consisting of dead trees adjacent to marshes are striking indicators of climate change, and marsh migration into retreating coastal forests is a primary mechanism for marsh survival in the face of global sea‐level rise. Models of coastal transgression typically assume inundation of a static topography and instantaneous conversion of forest to marsh with rising seas. In contrast, here we use four decades of satellite observations to show that many low‐elevation forests along the US mid‐Atlantic coast have survived despite undergoing relative sea‐level rise rates (RSLRR) that are among the fastest on Earth. Lateral forest retreat rates were strongly mediated by topography and seawater salinity, but not directly explained by spatial variability in RSLRR, climate, or disturbance. The elevation of coastal tree lines shifted upslope at rates correlated with, but far less than, contemporary RSLRR. Together, these findings suggest a multi‐decadal lag between RSLRR and land conversion that implies coastal ecosystem resistance. Predictions based on instantaneous conversion of uplands to wetlands may therefore overestimate future land conversion in ways that challenge the timing of greenhouse gas fluxes and marsh creation, but also imply that the full effects of historical sea‐level rise have yet to be realized. [ABSTRACT FROM AUTHOR]

Globally, forests are net carbon sinks that partly mitigates anthropogenic climate change. However, there is evidence of increasing weather-induced tree mortality, which needs to be better understood to improve forest management under future climate conditions. Disentangling drivers of tree mortality is challenging because of their interacting behavior over multiple temporal scales. In this study, we take a data-driven approach to the problem. We generate hourly temperate weather data using a stochastic weather generator to simulate 160,000 years of beech, pine, and spruce forest dynamics with a forest gap model. These data are used to train a generative deep learning model (a modified variational autoencoder) to learn representations of three-year-long monthly weather conditions (precipitation, temperature, and solar radiation) in an unsupervised way. We then associate these weather representations with years of high biomass loss in the forests and derive weather prototypes associated with such years. The identified prototype weather conditions are associated with 5–22% higher median biomass loss compared to the median of all samples, depending on the forest type and the prototype. When prototype weather conditions co-occur, these numbers increase to 10–25%. Our research illustrates how generative deep learning can discover compounding weather patterns associated with extreme impacts.

Forests play a crucial role as the primary sink for greenhouse gases, and forest mortality significantly impacts the carbon sequestration capacity of forest ecosystems. A single type of forest mortality model has been developed, and its model variables are incomplete, leading to significant bias in mortality prediction. To address this limitation, this study harnessed data collected from 773 permanent plots situated in Zhejiang Province, China, spanning a period from 2009 to 2019. The primary objectives were to pinpoint the key variables influencing forest mortality and to construct forest mortality prediction models utilizing both traditional regression methods and machine learning techniques, ultimately aiming to provide a theoretical basis for forest management practices and future predictions. Four basic linear regression models were used in this study: Linear Regression (LR), Akaike Information Criterion (AIC) Stepwise Regression, Ridge Regression, and Lasso Regression. Four machine learning models, Gradient Boosting Regression (GBR), Random Forest (RF), Support Vector Regression (SVR), and Multilayer Perceptron (MLP), were used to model stand mortality. Mortality was used as the dependent variable, and environmental factors such as topographic factors, soil composition, stand characteristics, and climatic variables were used as independent variables. The findings unveiled that soil and stand-related factors exerted significant effects on the mortality rate, whereas terrain-related and climate factors did not exhibit statistical significance. The Random Forest model established by using stand age, tree height, ADBH, crown cover, humus layer thickness, and the biodiversity index has the highest fitting statistics such as R² and Mean Squared Error, indicating that it has a good fitting and prediction effect, which effectively predicts mortality at the stand level, and is a valuable tool for predicting changes in forest ecosystems, with practical value in estimating tree mortality to enhance forest management and planning. [ABSTRACT FROM AUTHOR]

Climate change‐triggered forest die‐off is an increasing threat to global forests and carbon sequestration but remains extremely challenging to predict. Tree growth resilience metrics have been proposed as measurable proxies of tree susceptibility to mortality. However, it remains unclear whether tree growth resilience can improve predictions of stand‐level mortality. Here, we use an extensive tree‐ring dataset collected at ~3000 permanent forest inventory plots, spanning 13 dominant species across the US Mountain West, where forests have experienced strong drought and extensive die‐off has been observed in the past two decades, to test the hypothesis that tree growth resilience to drought can explain and improve predictions of observed stand‐level mortality. We found substantial increases in growth variability and temporal autocorrelation as well declining drought resistance and resilience for a number of species over the second half of the 20th century. Declining resilience and low tree growth were strongly associated with cross‐ and within‐species patterns of mortality. Resilience metrics had similar explicative power compared to climate and stand structure, but the covariance structure among predictors implied that the effect of tree resilience on mortality could partially be explained by stand and climate variables. We conclude that tree growth resilience offers highly valuable insights on tree physiology by integrating the effect of stressors on forest mortality but may have only moderate potential to improve large‐scale projections of forest die‐off under climate change. [ABSTRACT FROM AUTHOR]

Forests are facing unprecedented stressors, evidenced by increases in the rate of forest mortality. Characterizing the state of forest ecosystems and their responses to disturbances remains a complex and crucial task. Existing methodologies have rarely been evaluated in real-world ecosystems due to challenges such as limitations in data availability and analytical techniques. To address these gaps, this study employs remotely sensed spatio-temporal data to identify early warning signals of forest mortality using satellite imagery. Utilizing local spatial autocorrelation methods, specifically local Geary's c and local Moran's I, a robust approach that yielded consistent results across multiple study sites is developed. This approach successfully generated early warning signals based on time-series analysis of local spatial autocorrelation metrics, providing up to a two-year advance notice of impending forest mortality events. The results demonstrated that the proposed approach could outperform previous techniques in reliably generating early warning signals of forest mortality, as shown by significant trend analysis. Additionally, a new R software package, “stew”, is introduced that is designed to facilitate user-friendly spatio-temporal analysis of ecosystem state changes. In summary, this study corroborates the potential of spatio-temporal indicators as valuable tools for predicting climate-induced forest mortality up to two years in advance.

Climate, disturbance, vegetation response and their interaction are key factors in predicting the distribution and function of ecosystems across landscapes. A range of factors, operating through different pathways, are amplifying the feedbacks in this three‐way interaction.In the western USA, the relative strength of the influence of climate versus vegetation on fire activity varies spatially, realizing a diversity of fire regimes and fire‐selected species traits under historical conditions of climate–fire–vegetation interactions.Human intervention, via land use and fire‐exclusion, has homogenized frequent‐fire‐adapted forests in terms of structure and composition. Climate change is reinforcing the homogenization directly via increasing temperatures and drought and indirectly through climate‐driven tree mortality. The net effect will be forming novel climate–fire–vegetation interactions that act to homogenize fire regimes and catalyse large‐scale forest loss.While long‐term persistence of tree species in a given location may not be possible due to directional change of climate, slowing the rate of wildfire‐driven forest cover loss and maximizing the in‐situ persistence of a diversity of species will allow forest ecosystems to respond more incrementally to changing climate and provide an opportunity for ecosystem reassembly to occur from a large pool of species.As climate continues to change, management to resist wildfire‐driven forest cover loss may hinge on reducing forest density and creating a higher level of heterogeneity to reach the resistance and resilience exhibited by pre‐fire‐exclusion forests. Management operations should better leverage disturbance while strategically deploying silvicultural treatments to increase managed and prescribed fire.Further research is needed to improve our capacity for quantifying key mechanisms and system responses involved in the climate–fire–vegetation interactions and predicting how best to allocate resources to manage for functional forests. Read the free Plain Language Summary for this article on the Journal blog. [ABSTRACT FROM AUTHOR]

The Zagros forests in Iran are currently experiencing an exacerbation of climate-induced mortality, placing the Persian squirrel, a keystone species reliant on these ecosystems, in jeopardy. Addressing this imminent threat, our research employed a spatial prioritization methodology, integrating assessments of habitat suitability and mortality risk. Utilizing a weighted ensemble approach, incorporating the strengths of diverse models and expert rules, we discerned that approximately 62% of surveyed forests are at risk, with 7% classified as high risk and 17% as very high risk. Notably, 83% of the forests exhibited varying degrees of habitat suitability, with 11% and 12% demonstrating high and very high suitability, respectively. Employing a conservation prioritization framework, we systematically categorized habitats into priority classes, with 8%, 17%, 29%, and 46% assigned to very high, high, moderate, and low conservation priority classes, respectively. Significantly, areas classified as very high priority demand immediate restoration efforts due to ongoing mortality, while other priority classes underscore the importance of protection and prevention in unaffected habitats. Acknowledging the irreversible nature of current climatic conditions in the Zagros forests, our strategic emphasis aligns with conservation triage principles, prioritizing the preservation of intact habitats yet to succumb to irreversible mortality.

Climate change is predicted to lead to increasingly intense and hotter droughts, causing physiological weakness followed by forest decline in many regions of the world. Long- and short-range remote sensing (satellites and unmanned aerial vehicles, commonly called drones) can sense drought-induced changes in vegetation. Although several studies have addressed forest decline events, none have analyzed the forest decline attributable to climate change using remote sensing in a concise manner. A bibliometric analysis was carried out to characterize the scientific production reported in the Web of Science repository. The search descriptors were a combination of keywords related to forest decline and remote sensing. The results showed 278 articles published between 1989 and 2021 in 92 journals, with an average annual increase of 31%. A total of 29 nodes and 220 scientific collaboration links were located, mainly led by researchers from USA, Germany and China. Keyword analysis using World-TreeMap reflected the association of different key forest decline phenomena such as drought stress and climate change. Although the use of satellite information to study and understand forest decline has been reported for just over three decades, the most notable feature of the present research was the limited role of drones with only 5 studies. This reveals an area of opportunity to take advantage of the main strengths of drones, i.e., spatial and temporal resolution, low cost compared to manned flights, and centimeter accuracy. Therefore, it is strongly recommended to increase studies to improve the use of multispectral sensors, thermal and LiDAR technology for long-term monitoring of forest decline related to climate change.

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European forests are an important source for timber production, human welfare, income, protection and biodiversity. During the last two decades, Europe has experienced a number of droughts which have been exceptional within the last 500 years, both in terms of duration and intensity. These droughts seem to leave remarkable imprints on the mortality dynamics of European forests. However, systematic observations on tree decline, with emphasis on a single species, has been scarce so far so that our understanding of mortality dynamics and drought occurrence is still limited at a continental scale.Here, we make use of the ICP Forest crown defoliation dataset, permitting us to retrospectively monitor tree mortality for all major conifers, major broadleaves, as well as a pooled dataset of minor tree species in Europe. In total, we analysed more than three million observations gathered during the last 25 years and employed a high‐resolution drought index which can assess soil moisture anomaly based on a hydrological water‐balance and runoff model.We found overall and species‐specific increasing trends in mortality rates, accompanied by decreasing soil moisture. A generalized linear mixed model identified a previous‐year soil moisture anomaly as the most important driver of mortality patterns in conifers, but the response was not uniform across the numerous analysed plots.We conclude that mortality patterns in European forests are currently reaching a concerning upward trend which could be further accelerated by global change‐type droughts in the near future. [ABSTRACT FROM AUTHOR]

Forests play a crucial role as the primary sink for greenhouse gases, and forest mortality significantly impacts the carbon sequestration capacity of forest ecosystems. A single type of forest mortality model has been developed, and its model variables are incomplete, leading to significant bias in mortality prediction. To address this limitation, this study harnessed data collected from 773 permanent plots situated in Zhejiang Province, China, spanning a period from 2009 to 2019. The primary objectives were to pinpoint the key variables influencing forest mortality and to construct forest mortality prediction models utilizing both traditional regression methods and machine learning techniques, ultimately aiming to provide a theoretical basis for forest management practices and future predictions. Four basic linear regression models were used in this study: Linear Regression (LR), Akaike Information Criterion (AIC) Stepwise Regression, Ridge Regression, and Lasso Regression. Four machine learning models, Gradient Boosting Regression (GBR), Random Forest (RF), Support Vector Regression (SVR), and Multilayer Perceptron (MLP), were used to model stand mortality. Mortality was used as the dependent variable, and environmental factors such as topographic factors, soil composition, stand characteristics, and climatic variables were used as independent variables. The findings unveiled that soil and stand-related factors exerted significant effects on the mortality rate, whereas terrain-related and climate factors did not exhibit statistical significance. The Random Forest model established by using stand age, tree height, ADBH, crown cover, humus layer thickness, and the biodiversity index has the highest fitting statistics such as R² and Mean Squared Error, indicating that it has a good fitting and prediction effect, which effectively predicts mortality at the stand level, and is a valuable tool for predicting changes in forest ecosystems, with practical value in estimating tree mortality to enhance forest management and planning.

Tree mortality rates appear to be increasing in moist tropical forests (MTFs) with significant carbon cycle consequences. Here, we review the state of knowledge regarding MTF tree mortality, create a conceptual framework with testable hypotheses regarding the drivers, mechanisms and interactions that may underlie increasing MTF mortality rates, and identify the next steps for improved understanding and reduced prediction. Increasing mortality rates are associated with rising temperature and vapor pressure deficit, liana abundance, drought, wind events, fire and, possibly, CO2 fertilization-induced increases in stand thinning or acceleration of trees reaching larger, more vulnerable heights. The majority of these mortality drivers may kill trees in part through carbon starvation and hydraulic failure. The relative importance of each driver is unknown. High species diversity may buffer MTFs against large-scale mortality events, but recent and expected trends in mortality drivers give reason for concern regarding increasing mortality within MTFs. Models of tropical tree mortality are advancing the representation of hydraulics, carbon and demography, but require more empirical knowledge regarding the most common drivers and their subsequent mechanisms. We outline critical datasets and model developments required to test hypotheses regarding the underlying causes of increasing MTF mortality rates, and improve prediction of future mortality under climate change.

Prolonged drought conditions in semi‐arid forests can lead to widespread vegetation stress and mortality. However, the distribution of these effects is not spatially uniform. We measured soil water potential at high spatial and temporal resolution using 112 sensors distributed across a ponderosa pine forest in northern Arizona, USA, during two abnormally dry years with below‐average total precipitation. We used the data to assess the effects of fore‐summer drought period on the timing, magnitude, and extent of drying throughout the top 100 cm of the soil profile. Additionally, we use high spatial resolution terrestrial lidar measurements of forest structure to develop relationships between soil drying and fine‐scale forest structure. We find that increasing drought from 2019 to 2020 caused significantly earlier onset of soil dying at all depths (25, 50 and 100 cm) and more days below a critical drying threshold for ponderosa pine. Additionally, our results show that significantly drier soils are found in areas with higher stand‐level basal area, canopy cover and tree density, and shorter trees. Our results from the unprecedented spatial and temporal resolution data suggest that tailored restoration thinning with specific tree density and size parameters can be used to increase and prolong the availability of deep soil water to trees during drought. [ABSTRACT FROM AUTHOR]

Mapping geographic mosaics of genetic variation and their consequences via genotype x environment interactions at large extents and high resolution has been limited by the scalability of DNA sequencing. Here, we address this challenge for cytotype (chromosome copy number) variation in quaking aspen, a drought‐impacted foundation tree species. We integrate airborne imaging spectroscopy data with ground‐based DNA sequencing data and canopy damage data in 391 km2 of southwestern Colorado. We show that (1) aspen cover and cytotype can be remotely sensed at 1 m spatial resolution, (2) the geographic mosaic of cytotypes is heterogeneous and interdigitated, (3) triploids have higher leaf nitrogen, canopy water content, and carbon isotope shifts (δ13C) than diploids, and (4) canopy damage varies among cytotypes and depends on interactions with topography, canopy height, and trait variables. Triploids are at higher risk in hotter and drier conditions. [ABSTRACT FROM AUTHOR]

Sensitivity of forest mortality to drought in carbon‐dense tropical forests remains fraught with uncertainty, while extreme droughts are predicted to be more frequent and intense. Here, the potential of temporal autocorrelation of high‐frequency variability in Landsat Enhanced Vegetation Index (EVI), an indicator of ecosystem resilience, to predict spatial and temporal variations of forest biomass mortality is evaluated against in situ census observations for 64 site‐year combinations in Costa Rican tropical dry forests during the 2015 ENSO drought. Temporal autocorrelation, within the optimal moving window of 24 months, demonstrated robust predictive power for in situ mortality (leave‐one‐out cross‐validation R2 = 0.54), which allows for estimates of annual biomass mortality patterns at 30 m resolution. Subsequent spatial analysis showed substantial fine‐scale heterogeneity of forest mortality patterns, largely driven by drought intensity and ecosystem properties related to plant water use such as forest deciduousness and topography. Highly deciduous forest patches demonstrated much lower mortality sensitivity to drought stress than less deciduous forest patches after elevation was controlled. Our results highlight the potential of high‐resolution remote sensing to "fingerprint" forest mortality and the significant role of ecosystem heterogeneity in forest biomass resistance to drought. [ABSTRACT FROM AUTHOR]

Earthquakes can produce significant tree mortality, and consequently affect regional carbon dynamics. Unfortunately, detailed studies quantifying the influence of earthquake on forest mortality are currently rare. The committed forest biomass carbon loss associated with the 2008 Wenchuan earthquake in China is assessed by a synthetic approach in this study that integrated field investigation, remote sensing analysis, empirical models and Monte Carlo simulation. The newly developed approach significantly improved the forest disturbance evaluation by quantitatively defining the earthquake impact boundary and detailed field survey to validate the mortality models. Based on our approach, a total biomass carbon of 10.9 Tg·C was lost in Wenchuan earthquake, which offset 0.23% of the living biomass carbon stock in Chinese forests. Tree mortality was highly clustered at epicenter, and declined rapidly with distance away from the fault zone. It is suggested that earthquakes represent a significant driver to forest carbon dynamics, and the earthquake-induced biomass carbon loss should be included in estimating forest carbon budgets.

Despite great concern for drought‐driven forest mortality, the effects of frequent low‐intensity droughts have been largely overlooked in the boreal forest because of their negligible impacts over the short term. In this study, we used data from 6876 permanent plots distributed across most of the Canadian boreal zone to assess the effects of repeated low‐intensity droughts on forest mortality. Specifically, we compared the relative impact of sequential years under low‐intensity dry conditions with the effects of variables related to the intensity of dry conditions, stand characteristics, and local climate. Then, we searched for thresholds in forest mortality as a function of the number of years between two forest surveys affected by dry conditions of any intensity. Our results showed that, in general, frequent low‐intensity dry conditions had stronger effects on forest mortality than the intensity of the driest conditions in the plot. Frequent low‐intensity dry conditions acted as an inciting factor of forest mortality exacerbated by stand characteristics and environmental conditions. Overall, the mortality of forests dominated by shade‐tolerant conifers was significantly and positively related to frequent low‐intensity dry conditions, supporting, in some cases, the existence of thresholds delimiting contrasting responses to drought. In mixtures with broadleaf species, however, sequential dry conditions had a negligible impact. The effects of frequent dry conditions on shade‐intolerant forests mainly depended on local climate, inciting or mitigating the mortality of forests located in wet places and dominated by broadleaf species or jack pine, respectively. Our results highlight the importance of assessing not only climate‐driven extreme events but also repeated disturbances of low intensity. In the long term, the smooth response of forests to dry conditions might abruptly change leading to disproportional mortality triggered by accumulated stress conditions. Forest and wildlife managers should consider the cumulative effects of climate change on mortality to avoid shortfalls in timber and habitat. [ABSTRACT FROM AUTHOR]

Abiotic forest disturbances are an important driver of ecosystem dynamics. In Europe, storms and fires have been identified as the most important abiotic disturbances in the recent past. Yet, how strongly these agents drive local disturbance regimes compared to other agents (e.g., biotic, human) remains unresolved. Furthermore, whether storms and fires are responsible for the observed increase in forest disturbances in Europe is debated. Here, we provide quantitative evidence for the prevalence of storm and fire disturbances in Europe 1986–2016. For 27 million disturbance patches mapped from satellite data, we determined whether they were caused by storm or fire, using a random forest classifier and a large reference dataset of true disturbance occurrences. We subsequently analyzed patterns of disturbance prevalence (i.e., the share of an agent on the overall area disturbed) in space and time. Storm‐ and fire‐related disturbances each accounted for approximately 7% of all disturbances recorded in Europe in the period 1986–2016. Storm‐related disturbances were most prevalent in western and central Europe, where they locally accounted for >50% of all disturbances, but we also identified storm‐related disturbances in south‐eastern and eastern Europe. Fire‐related disturbances were a major disturbance agent in southern and south‐eastern Europe, but fires also occurred in eastern and northern Europe. The prevalence and absolute area of storm‐related disturbances increased over time, whereas no trend was detected for fire‐related disturbances. Overall, we estimate an average of 127,716 (97,680–162,725) ha of storm‐related disturbances per year and an average of 141,436 (107,353–181,022) ha of fire‐related disturbances per year. We conclude that abiotic disturbances caused by storm and fire are important drivers of forest dynamics in Europe, but that their influence varies substantially by region. Our analysis further suggests that increasing storm‐related disturbances are an important driver of Europe's changing forest disturbance regimes. [ABSTRACT FROM AUTHOR]

Most North American forests are at some stage of post-disturbance regrowth, subject to a changing climate, and exhibit growth and mortality patterns that may not be closely coupled to annual environmental conditions. Distinguishing the possibly interacting effects of these processes is necessary to put short-term studies in a longer term context, and particularly important for the carbon-dense, fire-prone boreal forest. The goals of this study were to combine dendrochronological sampling, inventory records, and machine-learning algorithms to understand how tree growth and death have changed at one highly studied site (Northern Old Black Spruce, NOBS) in the central Canadian boreal forest. Over the 1999-2012 inventory period, mean tree diameter increased even as stand density and basal area declined significantly. Tree mortality averaged 1.4 ± 0.6% yr-(1), with most mortality occurring in medium-sized trees; new recruitment was minimal. There have been at least two, and probably three, significant influxes of new trees since stand initiation, but none in recent decades. A combined tree ring chronology constructed from sampling in 2001, 2004, and 2012 showed several periods of extreme growth depression, with increased mortality lagging depressed growth by ~5 years. Higher minimum and maximum air temperatures exerted a negative influence on tree growth, while precipitation and climate moisture index had a positive effect; both current- and previous-year data exerted significant effects. Models based on these variables explained 23-44% of the ring-width variability. We suggest that past climate extremes led to significant mortality still visible in the current forest structure, with decadal dynamics superimposed on slower patterns of fire and succession. These results have significant implications for our understanding of previous work at NOBS, the carbon sequestration capability of old-growth stands in a disturbance-prone landscape, and the sustainable management of regional forests in a changing climate.

Global warming is altering climate patterns and the frequency and magnitude of heat and drought events affecting ecosystems worldwide. One of the effects of these changes is tree mortality driven by heat and drought, which have effects in forest ecosystem functions, services and biodiversity. Therefore, systematic observations and georeferenced data on tree mortality is a fundamental prerequisite for a more comprehensive understanding of the complex interactions between climate and forests. Tree mortality is a complex process for which literature presents major knowledge gaps, making predictions on the fate of climate change challenging. Some of the gaps are due to limited spatio-temporal data on tree mortality. Despite extensive tree mortality and forest dieback, associated with drought and temperature stress, have been reported in Europe, a publicly available systematic collection of georeferenced data reporting tree mortality is lacking. The dataset presented in this paper is a contribution to mitigate the lack of information on tree mortality. Our dataset builds on scientific and peer-reviewed literature and provides a georeferenced set of documented tree mortality occurrences in the period 1970-2017 in Europe. The aim of this study is to describe the creation of the dataset and to provide the data file to interested users.

Abstract Climate change is altering the conditions for tree recruitment, growth, and survival, and impacting forest community composition. Across southeast Alaska, USA, and British Columbia, Canada, Callitropsis nootkatensis (Alaska yellow‐cedar) is experiencing extensive climate change‐induced canopy mortality due to fine‐root death during soil freezing events following warmer winters and the loss of insulating snowpack. Here, we examine the effects of ongoing, climate‐driven canopy mortality on forest community composition and identify potential shifts in stand trajectories due to the loss of a single canopy species. We sampled canopy and regenerating forest communities across the extent of C. nootkatensis decline in southeast Alaska to quantify the effects of climate, community, and stand‐level drivers on C. nootkatensis canopy mortality and regeneration as well as postdecline regenerating community composition. Across the plot network, C. nootkatensis exhibited significantly higher mortality than co‐occurring conifers across all size classes and locations. Regenerating community composition was highly variable but closely related to the severity of C. nootkatensis mortality. Callitropsis nootkatensis canopy mortality was correlated with winter temperatures and precipitation as well as local soil drainage, with regenerating community composition and C. nootkatensis regeneration abundances best explained by available seed source. In areas of high C. nootkatensis mortality, C. nootkatensis regeneration was low and replaced by Tsuga. Our study suggests that climate‐induced forest mortality is driving alternate successional pathways in forests where C. nootkatensis was once a major component. These pathways are likely to lead to long‐term shifts in forest community composition and stand dynamics. Our analysis fills a critical knowledge gap on forest ecosystem response and rearrangement following the climate‐driven decline of a single species, providing new insight into stand dynamics in a changing climate. As tree species across the globe are increasingly stressed by climate change‐induced alteration of suitable habitat, identifying the autecological factors contributing to successful regeneration, or lack thereof, will provide key insight into forest resilience and persistence on the landscape.

Bark beetles naturally inhabit forests and can cause large-scale tree mortality when they reach epidemic population numbers. A recent epidemic (1990s–2010s), primarily driven by mountain pine beetles (Dendroctonus ponderosae), was a leading mortality agent in western United States forests. Predictive models of beetle populations and their impact on forests largely depend on host related parameters, such as stand age, basal area, and density. We hypothesized that bark beetle attack patterns are also dependent on inferred beetle population densities: large epidemic populations of beetles will preferentially attack large-diameter trees, and successfully kill them with overwhelming numbers. Conversely, small endemic beetle populations will opportunistically attack stressed and small trees. We tested this hypothesis using 12 years of repeated field observations of three dominant forest species (lodgepole pine Pinus contorta, Engelmann spruce Picea engelmannii, and subalpine fir Abies lasiocarpa) in subalpine forests of southeastern Wyoming paired with a Bayesian modeling approach. The models provide probabilistic predictions of beetle attack patterns that are free of assumptions required by frequentist models that are often violated in these data sets. Furthermore, we assessed seedling/sapling regeneration in response to overstory mortality and hypothesized that higher seedling/sapling establishment occurs in areas with highest overstory mortality because resources are freed from competing trees. Our results indicate that large-diameter trees were more likely to be attacked and killed by bark beetles than small-diameter trees during epidemic years for all species, but there was no shift toward preferentially attacking small-diameter trees in post-epidemic years. However, probabilities of bark beetle attack and mortality increased for small diameter lodgepole pine and Engelmann spruce trees in post-epidemic years compared to epidemic years. We also show an increase in overall understory growth (graminoids, forbs, and shrubs) and seedling/sapling establishment in response to beetle-caused overstory mortality, especially in lodgepole pine dominated stands. Our observations provide evidence of the trajectories of attack and mortality as well as early forest regrowth of three common tree species during the transition from epidemic to post-epidemic stages of bark beetle populations in the field.

Wind is the leading disturbance agent in European forests, and the magnitude of wind impacts on forest mortality has increased over recent decades. However, the atmospheric triggers behind severe winds in Western Europe (large‐scale cyclones) differ from those in Southeastern Europe (small‐scale convective instability). This geographic difference in wind drivers alters the spatial scale of resulting disturbances and potentially the sensitivity to climate change. Over the 20th century, the severity and prevalence of cyclone‐induced windstorms have increased while the prevalence of atmospheric instability has decreased and thus, the trajectory of Europe‐wide windthrow remains uncertain. To better predict forest sensitivity and trends of windthrow disturbance we used dendrochronological methods to reconstruct 140 years of disturbance history in beech‐dominated primary forests of Central and Eastern Europe. We compared generalized linear mixed models of these disturbance time series to determine whether large‐scale cyclones or small‐scale convective storms were more responsible for disturbance severity while also accounting for topography and stand character variables likely to influence windthrow susceptibility. More exposed forests, forests with a longer absence of disturbance, and forests lacking recent high severity disturbance showed increased sensitivity to both wind drivers. Large‐scale cyclone‐induced windstorms were the main driver of disturbance severity at both the plot and stand scale (0.1–∼100 ha) whereas convective instability effects were more localized (0.1 ha). Though the prevalence and severity of cyclone‐induced windstorms have increased over the 20 century, primary beech forests did not display an increase in the severity of windthrow observed over the same period. Plain Language Summary: Two main atmospheric patterns are driving European windthrow with large‐scale winter storms being more prevalent in Western Europe and summer thunderstorm‐generated winds being more prevalent in Eastern Europe. In central Europe, most forests display a mixed‐severity disturbance regime indicating that both large‐ and small‐scale disturbances are occurring. However, few studies have been conducted looking at the prevalence of large‐scale winter windstorms and small‐scale summer thunderstorms. Here we found evidence for both, but recently large‐scale winter windstorms have had a greater impact. Key Points: Windstorms and convective instability drive primary forest windthrow damageTopographic exposure and time and severity of last disturbance moderate windthrowWindstorms create higher severity windthrow than convective instability [ABSTRACT FROM AUTHOR]

Reduced forest mortality and increased streamflow have been promoted as hydrologic benefits of forest fuel treatments in water‐limited systems. These benefits, however, are often quite variable because they both rely upon the use of water made available through tree‐scale reductions in evapotranspiration. In this study, we examined whether forest mortality benefits and streamflow benefits from fuel treatments offset one another, because the allocation of unused water for one benefit implies less availability of that water for the other benefit. To do this, we took advantage of two paired‐watershed experiments in the Kings River Experimental Watersheds located in the southern Sierra Nevada. The fuel treatments, which included mechanical thinning and prescribed fire, began in 2012 and coincided with the 2012–2016 California drought and related forest mortality event. We found that in the higher‐elevation Bull watersheds, fuel treatments decreased forest mortality but had no effect on annual streamflow. In the lower‐elevation Providence watersheds, we observed the opposite result, as fuel treatments had no effect on forest mortality but depending on the model, increased annual streamflow at 95% and 90% confidence. The results suggest that the water made available from fuel treatments followed different hydrological pathways through the watersheds, with the water being taken up by neighbouring vegetation and decreasing water stress in Bull, and the water contributing to streamflow in Providence. These findings suggest that fuel treatments in water‐limited systems may not provide full hydrologic benefits to both forest mortality and streamflow concurrently in a given watershed. [ABSTRACT FROM AUTHOR]

In recent decades, intense droughts, insect outbreaks, and wildfires have led to decreasing tree growth and increasing mortality in many temperate forests. We compared annual tree-ring width data from 1,097 populations in the coterminous United States to climate data and evaluated site-specific tree responses to climate variations throughout the 20th century. For each population, we developed a climate-driven growth equation by using climate records to predict annual ring widths. Forests within the southwestern United States appear particularly sensitive to drought and warmth. We input 21st century climate projections to the equations to predict growth responses. Our results suggest that if temperature and aridity rise as they are projected to, southwestern trees will experience substantially reduced growth during this century. As tree growth declines, mortality rates may increase at many sites. Increases in wildfires and bark-beetle outbreaks in the most recent decade are likely related to extreme drought and high temperatures during this period. Using satellite imagery and aerial survey data, we conservatively calculate that ≈ 2.7% of southwestern forest and woodland area experienced substantial mortality due to wildfires from 1984 to 2006, and ≈ 7.6% experienced mortality associated with bark beetles from 1997 to 2008. We estimate that up to ≈ 18% of southwestern forest area (excluding woodlands) experienced mortality due to bark beetles or wildfire during this period. Expected climatic changes will alter future forest productivity, disturbance regimes, and species ranges throughout the Southwest. Emerging knowledge of these impending transitions informs efforts to adaptively manage southwestern forests.

Greenhouse gas emissions have significantly altered global climate, and will continue to do so in the future. Increases in the frequency, duration, and/or severity of drought and heat stress associated with climate change could fundamentally alter the composition, structure, and biogeography of forests in many regions. Of particular concern are potential increases in tree mortality associated with climate-induced physiological stress and interactions with other climate-mediated processes such as insect outbreaks and wildfire. Despite this risk, existing projections of tree mortality are based on models that lack functionally realistic mortality mechanisms, and there has been no attempt to track observations of climate-driven tree mortality globally. Here we present the first global assessment of recent tree mortality attributed to drought and heat stress. Although episodic mortality occurs in the absence of climate change, studies compiled here suggest that at least some of the world's forested ecosystems already may be responding to climate change and raise concern that forests may become increasingly vulnerable to higher background tree mortality rates and die-off in response to future warming and drought, even in environments that are not normally considered water-limited. This further suggests risks to ecosystem services, including the loss of sequestered forest carbon and associated atmospheric feedbacks. Our review also identifies key information gaps and scientific uncertainties that currently hinder our ability to predict tree mortality in response to climate change and emphasizes the need for a globally coordinated observation system. Overall, our review reveals the potential for amplified tree mortality due to drought and heat in forests worldwide.

Fog phenomena and their associated meteorological variables were continuously monitored during 4 years in an evergreen laurisilva cloud forest of the Anaga Massif Biosphere Reserve (Tenerife, Canary Islands), in order to establish its current dynamics. Fog was more frequent during night through early morning and in the afternoon, and particularly from May until September, coincidental with a frequent immersion of the 1025 m a.s.l. experimental site in the cloud layer of wind‐driven stratocumulus. The concomitant meteorological conditions during different fog regimes, characterized according to visibility (Ω) ranges, were compared with those when fog was absent. The presence of fog was associated with a significant reduction in global solar radiation, Rg, increased wind speed, and lower and more stable ambient temperatures. The foggy versus fog‐free hourly medians of Rg were found to be linearly related, whereas the proportion of median Rg reduction due to fog varied logarithmically with Ω. However, foggy versus fog‐free extreme values of the hourly Rg distributions departed from such a linear trend. By contrast, hourly temperatures during foggy versus fog‐free periods behaved linearly for most of the Ω range, except for very dense fog, Ω ≤ 100 m. Transpiration of the canopy, intermittently wetted due to interception of both rain and fog water droplets, was determined by quantifying the water balance at leaf scale with a mathematical model for the two representative hypostomatous species present at the site: the arboreal shrub Erica platycodon, with needle‐like leaves, and the laurophyll tree Myrica faya. Both tree transpiration and evaporation of the intercepted fog water were predictively higher during summer. By contrast, transpiration was reduced during February, in agreement with a 1 year period of sap velocity measurements, and was not appreciably affected by soil moisture content. The consequences of an anticipated downward shift of the stratocumulus cloud layer and of various projected Representative Concentration Pathways (RCPs) scenarios in the Macaronesian area were simulated, yielding in all cases a significant rise in transpiration for both species. Particularly, the simulated RCPs scenarios implied 29%–73% increments in transpiration from the actual values. Because fog is concomitant with lower temperatures and vapour pressure deficit, the modification of its current distribution as a consequence of climate change may have a direct effect on such associated meteorological variables, and therefore a meaningful impact in the water relations of the laurel cloud forests. [ABSTRACT FROM AUTHOR]

Summary: Growing evidence indicates that tree‐stem methane (CH4) emissions may be an important and unaccounted‐for component of local, regional and global carbon (C) budgets. Studies to date have focused on upland and freshwater swamp‐forests; however, no data on tree‐stem fluxes from estuarine species currently exist.Here we provide the first‐ever mangrove tree‐stem CH4 flux measurements from  >50 trees (n = 230 measurements), in both standing dead and living forest, from a region suffering a recent large‐scale climate‐driven dieback event (Gulf of Carpentaria, Australia).Average CH4 emissions from standing dead mangrove tree‐stems was 249.2 ± 41.0 μmol m−2 d−1 and was eight‐fold higher than from living mangrove tree‐stems (37.5 ± 5.8 μmol m−2 d−1). The average CH4 flux from tree‐stem bases (c. 10 cm aboveground) was 1071.1 ± 210.4 and 96.8 ± 27.7 μmol m−2 d−1 from dead and living stands respectively. Sediment CH4 fluxes and redox potentials did not differ significantly between living and dead stands. Our results suggest both dead and living tree‐stems act as CH4 conduits to the atmosphere, bypassing potential sedimentary oxidation processes.Although large uncertainties exist when upscaling data from small‐scale temporal measurements, we estimated that dead mangrove tree‐stem emissions may account for c. 26% of the net ecosystem CH4 flux. [ABSTRACT FROM AUTHOR]

Societal Impact Statement: Drought plays a conspicuous role in forest mortality, and is expected to become more severe in future climate scenarios. Recent surges in drought‐associated forest tree mortality have been documented worldwide. For example, recent droughts in California and Texas killed approximately 129 million and 300 million trees, respectively. Drought has also induced acute pine tree mortality across east‐central China, and across extensive areas in southwest China. Understanding the biological processes that enable trees to modify wood development to mitigate the adverse effects of drought will be crucial for the development of successful strategies for future forest management and conservation. Summary Drought is a recurrent stress to forests, causing periodic forest mortality with enormous economic and environmental costs. Wood is the water‐conducting tissue of tree stems, and trees modify wood development to create anatomical features and hydraulic properties that can mitigate drought stress. This modification of wood development can be seen in tree rings where not only the amount of wood but also the morphology of the water‐conducting cells are modified in response to environmental conditions. In this review, we provide an overview of how trees conduct water, and how trees modify wood development to affect water conduction properties in response to drought. We discuss key needs for new research, and how new knowledge of wood formation can play a role in the conservation of forests under threat by climate change. [ABSTRACT FROM AUTHOR]

Climate change is altering the conditions for tree recruitment, growth, and survival, and impacting forest community composition. Across southeast Alaska, USA, and British Columbia, Canada, Callitropsis nootkatensis (Alaska yellow‐cedar) is experiencing extensive climate change‐induced canopy mortality due to fine‐root death during soil freezing events following warmer winters and the loss of insulating snowpack. Here, we examine the effects of ongoing, climate‐driven canopy mortality on forest community composition and identify potential shifts in stand trajectories due to the loss of a single canopy species. We sampled canopy and regenerating forest communities across the extent of C. nootkatensis decline in southeast Alaska to quantify the effects of climate, community, and stand‐level drivers on C. nootkatensis canopy mortality and regeneration as well as postdecline regenerating community composition. Across the plot network, C. nootkatensis exhibited significantly higher mortality than co‐occurring conifers across all size classes and locations. Regenerating community composition was highly variable but closely related to the severity of C. nootkatensis mortality. Callitropsis nootkatensis canopy mortality was correlated with winter temperatures and precipitation as well as local soil drainage, with regenerating community composition and C. nootkatensis regeneration abundances best explained by available seed source. In areas of high C. nootkatensis mortality, C. nootkatensis regeneration was low and replaced by Tsuga. Our study suggests that climate‐induced forest mortality is driving alternate successional pathways in forests where C. nootkatensis was once a major component. These pathways are likely to lead to long‐term shifts in forest community composition and stand dynamics. Our analysis fills a critical knowledge gap on forest ecosystem response and rearrangement following the climate‐driven decline of a single species, providing new insight into stand dynamics in a changing climate. As tree species across the globe are increasingly stressed by climate change‐induced alteration of suitable habitat, identifying the autecological factors contributing to successful regeneration, or lack thereof, will provide key insight into forest resilience and persistence on the landscape. [ABSTRACT FROM AUTHOR]

Drought-induced tree mortality events are expected to increase in frequency under climate change. However, monitoring and modeling of tree mortality is limited by the high spatial variability in vegetation response to climatic drought stress and lack of physiologically meaningful stress variables that can be monitored at large scales. In this study, we test the hypothesis that relative water content (RWC) estimated by passive microwave remote sensing through vegetation optical depth can be used as an empirical indicator of tree mortality that both integrates variations in plant drought stress and is accessible across large areas. The hypothesis was tested in a recent severe drought in California, USA. The RWC showed a stronger threshold relationship with mortality than climatic water deficit (CWD) – a commonly used mortality indicator – although both relationships were noisy due to the coarse spatial resolution of the data (0.25° or approximately 25 km). In addition, the threshold for RWC was more uniform than that for CWD when compared between Northern and Southern regions of California. A random forests regression (machine learning) with 32 variables describing topography, climate, and vegetation characteristics predicted forest mortality extent i.e. fractional area of mortality (FAM) with satisfactory accuracy-coefficient of determination R test 2 = 0.66, root mean square error = 0.023. Importantly, RWC was more than twice as important as any other variable in the model in estimating mortality, confirming its strong link to mortality rates. Moreover, RWC showed a moderate ability to aid in forecasting mortality, with a relative importance of RWC measured one year in advance of mortality similar to that of other relevant explanatory variables measured in the mortality year. The results of this study present a promising new approach to estimate drought stress of forests linked to mortality risk. • Drought-driven tree mortality's link to remotely sensed indicators investigated • Relative water content using satellite-based vegetation optical depth estimated • Relative water content was the best predictor of mortality among 32 variables. [ABSTRACT FROM AUTHOR]

Climate change may reduce forest growth and increase forest mortality, which is connected to high carbon costs through reductions in gross primary production and net ecosystem exchange. Yet, the spatiotemporal patterns of vulnerability to both short‐term extreme events and gradual environmental changes are quite uncertain across the species' limits of tolerance to dryness. Such information is fundamental for defining ecologically relevant upper limits of species tolerance to drought and, hence, to predict the risk of increased forest mortality and shifts in species composition. We investigate here to what extent the impact of short‐ and long‐term environmental changes determines vulnerability to climate change of three evergreen conifers (Scots pine, silver fir, Norway spruce) and two deciduous hardwoods (European beech, sessile oak) tree species at their southernmost limits of distribution in the Mediterranean Basin. Finally, we simulated future forest growth under RCP 2.6 and 8.5 emission scenarios using a multispecies generalized linear mixed model. Our analysis provides four key insights into the patterns of species' vulnerability to climate change. First, site climatic marginality was significantly linked to the growth trends: increasing growth was related to less climatically limited sites. Second, estimated species‐specific vulnerability did not match their a priori rank in drought tolerance: Scots pine and beech seem to be the most vulnerable species among those studied despite their contrasting physiologies. Third, adaptation to site conditions prevails over species‐specific determinism in forest response to climate change. And fourth, regional differences in forests vulnerability to climate change across the Mediterranean Basin are linked to the influence of summer atmospheric circulation patterns, which are not correctly represented in global climate models. Thus, projections of forest performance should reconsider the traditional classification of tree species in functional types and critically evaluate the fine‐scale limitations of the climate data generated by global climate models. Current and forecasted trends in tree growth from temperate and boreal tree species growing at the southernmost limit of their natural distribution in Europe. The tree growth projections by 2100 revealed a generalized decrease in growth under the climatic conditions derived from the RCP 8.5 emission scenario. [ABSTRACT FROM AUTHOR]

Aim: Catastrophic forest mortality due to more extreme rainfall deficits and higher temperatures under future climate scenarios has been predicted. The aim of this study is to explore the magnitude of historical drought‐induced tree mortality under pre‐warming conditions. Location: North‐eastern Australia. Time period: 1845–2017. Major taxa studied: Trees. Methods: Field survey, historical analysis and climate analysis. Results: We present evidence of 18%–30% tree mortality from recent droughts across three regions of north‐eastern Australia with rainfall deficits less severe than earlier historical droughts. The corrected temperature record represents modest warming at the stations with long records in the vicinity of the study areas. In terms of rainfall deficit the most severe drought on record occurred in the early 20th century, and historical evidence confirms that this drought and earlier droughts before the advent of pastoralism coincided with substantial tree mortality. Main conclusions: Dramatic declines in woody biomass in response to drought historically occurred more than once a century and are a natural phenomenon in semi‐arid Australia. The magnitude of drought‐induced tree mortality under natural climate fluctuations requires further investigation in other continents. Widespread drought‐induced tree mortality is not just a recent global change phenomenon and has been underestimated as a natural ecological process. However, even more severe forest die‐off events from more extreme hotter droughts are predicted if Earth's warming proceeds as currently projected. [ABSTRACT FROM AUTHOR]

Highlights • Bole scorch height predicts attack by Dendroctonus valens and D. brevicomis. • Majority of D. valens attacks occur the first year post-fire. • Majority of D. brevicomis attacks occur after the first year post-fire. • Mortality rate of beetle attacked trees declines after the first year post-fire. • D. valens attack functions as a tree injury indicator similar to cambium kill. Abstract In ponderosa pine forests of western North America, wildfires are becoming more frequent and affecting larger areas, while prescribed fire is increasingly used to reduce fuels and mitigate potential wildfire severity. Both fire types leave trees that initially survive their burn injuries, but will eventually die. Predicting delayed tree mortality has received considerable research attention to aid in post-fire planning and management. The amount of crown scorched is recognized as the most useful variable for discriminating between trees that live or die, but models gain discrimination with additional variables such as bole scorch, bud or cambium necrosis, and post-fire bark beetle attack (Coleoptera: Curculionidae: Scolytinae). Here, logistic regression was used to determine what fire-injury variables are most associated with red turpentine beetle (RTB; Dendroctonus valens LeConte) , or western pine beetle (WPB; D. brevicomis LeConte) attack within three years post-fire. This was tested on 7343 ponderosa pine representing a wide diameter range from 18 wild and prescribed fires in Oregon and Washington, and repeated on a subset of 884 large trees >53.3 cm diameter. Bole scorch height was most associated with RTB or WPB attack on trees across all diameters, but model predictive ability was poor, whereas for pines >53.3 cm, the models provided moderate discrimination for predicting attack by each beetle. In addition, mortality models using crown scorch proportion and bole scorch proportion were compared to models with an additional variable for RTB, or WPB attack in year one, or attack by either beetle in year one, or year three. Models including any one of these beetle variables outperformed the models using just bole scorch and crown scorch proportions. For both tree diameter groups, the models including RTB year one performed similar to, or better than models with any other beetle variable, and are preferred for predicting delayed mortality because the RTB attack functions as an additional tree injury indicator similar to cambium kill, not captured by the bole scorch proportion, or crown scorch proportion variables. Furthermore, RTB attack can be assessed within the first year post-fire, and is much faster and easier to evaluate than direct sampling of cambium necrosis. [ABSTRACT FROM AUTHOR]

Droughts and heatwaves cause agricultural loss, forest mortality, and drinking water scarcity, especially when they occur simultaneously as combined events. Their predicted increase in recurrence and intensity poses serious threats to future food security. Still today, the knowledge of how droughts and heatwaves start and evolve remains limited, and so does our understanding of how climate change may affect them. Droughts and heatwaves have been suggested to intensify and propagate via land–atmosphere feedbacks. However, a global capacity to observe these processes is still lacking, and climate and forecast models are immature when it comes to representing the influences of land on temperature and rainfall. Key open questions remain in our goal to uncover the real importance of these feedbacks: What is the impact of the extreme meteorological conditions on ecosystem evaporation? How do these anomalies regulate the atmospheric boundary layer state (event self‐intensification) and contribute to the inflow of heat and moisture to other regions (event self‐propagation)? Can this knowledge on the role of land feedbacks, when available, be exploited to develop geo‐engineering mitigation strategies that prevent these events from aggravating during their early stages? The goal of our perspective is not to present a convincing answer to these questions, but to assess the scientific progress to date, while highlighting new and innovative avenues to keep advancing our understanding in the future. Droughts and heatwaves cause agricultural loss, forest mortality and drinking water scarcity, especially when they occur simultaneously as combined events. Their predicted increase in recurrence and intensity poses serious threats to future food security. Still today, the knowledge of how droughts and heatwaves start and evolve remains limited, and so does our understanding of how climate change may affect them. Our goal is to revisit the role of land feedbacks on the evolution of these extreme events, and highlight new and innovative avenues to keep advancing our understanding how droughts and heatwaves develop and propagate. [ABSTRACT FROM AUTHOR]

Global warming is altering climate patterns and the frequency and magnitude of heat and drought events affecting ecosystems worldwide. One of the effects of these changes is tree mortality driven by heat and drought, which have effects in forest ecosystem functions, services and biodiversity. Therefore, systematic observations and georeferenced data on tree mortality is a fundamental prerequisite for a more comprehensive understanding of the complex interactions between climate and forests. Tree mortality is a complex process for which literature presents major knowledge gaps, making predictions on the fate of climate change challenging. Some of the gaps are due to limited spatio-temporal data on tree mortality. Despite extensive tree mortality and forest dieback, associated with drought and temperature stress, have been reported in Europe, a publicly available systematic collection of georeferenced data reporting tree mortality is lacking. The dataset presented in this paper is a contribution to mitigate the lack of information on tree mortality. Our dataset builds on scientific and peer-reviewed literature and provides a georeferenced set of documented tree mortality occurrences in the period 1970-2017 in Europe. The aim of this study is to describe the creation of the dataset and to provide the data file to interested users. [ABSTRACT FROM AUTHOR]

Forest mortality has been widely observed across the globe during recent episodes of drought and extreme heat events. But the future of forest mortality remains poorly understood. While the direct effects of future climate and elevated CO _2 on forest mortality risk have been studied, the role of lateral subsurface water flow has rarely been considered. Here we demonstrated the fingerprint of lateral flow on the forest mortality risk of a riparian ecosystem using a coupled plant hydraulics-hydrology model prescribed with multiple Earth System Model projections of future hydroclimate. We showed that the anticipated water-saving and drought ameliorating effects of elevated CO _2 on mortality risk were largely compromised when lateral hydrological processes were considered. Further, we found lateral flow reduce ecosystem sensitivity to climate variations, by removing soil water excess during wet periods and providing additional water from groundwater storage during dry periods. These findings challenge the prevailing expectation of elevated CO _2 to reduce mortality risk and highlight the need to assess the effects of lateral flow exchange more explicitly moving forward with forest mortality projections.

[Display omitted] • New spatio-temporal indicators detect early warning signs of forest mortality. • Our method reliably identifies reduced resilience in forests for timely action. • Less data preprocessing required, improving critical transition detection. • User-friendly R package introduced for easy exploration of early warning signals. • Study offers actionable insights for effective forest management and conservation. Forests are facing unprecedented stressors, evidenced by increases in the rate of forest mortality. Characterizing the state of forest ecosystems and their responses to disturbances remains a complex and crucial task. Existing methodologies have rarely been evaluated in real-world ecosystems due to challenges such as limitations in data availability and analytical techniques. To address these gaps, this study employs remotely sensed spatio-temporal data to identify early warning signals of forest mortality using satellite imagery. Utilizing local spatial autocorrelation methods, specifically local Geary's c and local Moran's I , a robust approach that yielded consistent results across multiple study sites is developed. This approach successfully generated early warning signals based on time-series analysis of local spatial autocorrelation metrics, providing up to a two-year advance notice of impending forest mortality events. The results demonstrated that the proposed approach could outperform previous techniques in reliably generating early warning signals of forest mortality, as shown by significant trend analysis. Additionally, a new R software package, "stew", is introduced that is designed to facilitate user-friendly spatio-temporal analysis of ecosystem state changes. In summary, this study corroborates the potential of spatio-temporal indicators as valuable tools for predicting climate-induced forest mortality up to two years in advance. [ABSTRACT FROM AUTHOR]

Background and Objectives: Increased frequency and intensity of drought events are predicted to occur throughout the world because of climate change. These extreme climate events result in higher tree mortality and fraction of dead woody components, phenomena that are currently being reported worldwide as critical indicators of the impacts of climate change on forest diversity and function. In this paper, we assess the accuracy and processing times of ten machine learning (ML) techniques, applied to multispectral unmanned aerial vehicle (UAV) data to detect dead canopy woody components. Materials and Methods: This work was conducted on five secondary dry forest plots located at the Santa Rosa National Park Environmental Monitoring Super Site, Costa Rica. Results: The coverage of dead woody components at the selected secondary dry forest plots was estimated to range from 4.8% to 16.1%, with no differences between the successional stages. Of the ten ML techniques, the support vector machine with radial kernel (SVMR) and random forests (RF) provided the highest accuracies (0.982 vs. 0.98, respectively). Of these two ML algorithms, the processing time of SVMR was longer than the processing time of RF (8735.64 s vs. 989 s). Conclusions: Our results demonstrate that it is feasible to detect and quantify dead woody components, such as dead stands and fallen trees, using a combination of high-resolution UAV data and ML algorithms. Using this technology, accuracy values higher than 95% were achieved. However, it is important to account for a series of factors, such as the optimization of the tuning parameters of the ML algorithms, the environmental conditions and the time of the UAV data acquisition.

ABSTRACT Forested ecosystems throughout the world are experiencing increases in the incidence and magnitude of insect-induced tree mortality with large ecologic ramifications. Interestingly, correlations between water quality and the extent of tree mortality in Colorado montane ecosystems suggest compensatory effects from adjacent live vegetation that mute responses in less severely impacted forests. To this end, we investigated whether the composition of the soil bacterial community and associated functionality beneath beetle-killed lodgepole pine was influenced by the extent of surrounding tree mortality. The most pronounced changes were observed in the potentially active bacterial community, where alpha diversity increased in concert with surrounding tree mortality until mortality exceeded a tipping point of ~30 to 40%, after which diversity stabilized and decreased. Community structure also clustered in association with the extent of surrounding tree mortality with compositional trends best explained by differences in NH4+ concentrations and C/N ratios. C/N ratios, which were lower in soils under beetle-killed trees, further correlated with the relative abundance of putative nitrifiers and exoenzyme activity. Collectively, the response of soil microorganisms that drive heterotrophic respiration and decay supports observations of broader macroscale threshold effects on water quality in heavily infested forests and could be utilized as a predictive mechanism during analogous ecosystem disruptions. IMPORTANCE Forests around the world are succumbing to insect infestation with repercussions for local soil biogeochemistry and downstream water quality and quantity. This study utilized microbial community dynamics to address why we are observing watershed scale biogeochemical impacts from forest mortality in some impacted areas but not others. Through a unique “tree-centric” approach, we were able to delineate plots with various tree mortality levels within the same watershed to see if surviving surrounding vegetation altered microbial and biogeochemical responses. Our results suggest that forests with lower overall tree mortality levels are able to maintain “normal” ecosystem function, as the bacterial community appears resistant to tree death. However, surrounding tree mortality influences this mitigating effect with various linear and threshold responses whereupon the bacterial community and its function are altered. Our study lends insight into how microscale responses propagate upward into larger-scale observations, which may be useful for future predictions during analogous disruptions.

Extreme climatic events, including droughts and heatwaves, can trigger outbreaks of woodboring beetles by compromising host defenses and creating habitat conducive for beetle development. As the frequency, intensity, and duration of droughts are likely to increase in the future, beetle outbreaks are expected to become more common. The combination of drought and beetle outbreaks has the potential to alter ecosystem structure, composition, and function. Our aim was to investigate a potential outbreak of the native Eucalyptus longhorned borer, Phoracantha semipunctata (P. semipunctata), following one of the most severe droughts on record in the Northern Jarrah Forest of Southwestern Australia. Beetle damage and tissue moisture were examined in trees ranging from healthy to recently killed. Additionally, beetle population levels were examined in adjacent forest areas exhibiting severe and minimal canopy dieback. Severely drought-affected forest was associated with an unprecedented outbreak of P. semipunctata, with densities 80 times higher than those observed in surrounding healthier forest. Trees recently killed by drought had significantly lower tissue moisture and higher feeding damage and infestation levels than those trees considered healthy or in the process of dying. These results confirm the outbreak potential of P. semipunctata in its native Mediterranean-climate Eucalyptus forest under severe water stress, and indicate that continued drying will increase the likelihood of outbreaks.