Forest Mortality Research Articles

Climate-Induced Forest Mortality in the Tropical Pacific Islands: What Do We Really Know?

Climate-Induced Forest Mortality in the Tropical Pacific Islands: What Do We Really Know?

Tree crown defoliation in forest monitoring: concepts, findings, and new perspectives for a physiological approach in the face of climate change

Abstract Recurrent climate-driven disturbances impact on the health of European forests that reacted with increased tree dieback and mortality over the course of the last four decades. There is therefore large interest in predicting and understanding the fate and survival of forests under climate change. Forest conditions are monitored within the pan-European ICP Forests programme (UN-ECE International Co-operative Programme on Assessment and Monitoring of Air Pollution Effects on Forests) since the 1980s, with tree crown defoliation being the most widely used parameter. Defoliation is not a cause-specific indicator of tree health and vitality, and there is a need to connect defoliation levels with the physiological functioning of trees. The physiological responses connected to tree crown defoliation are species-specific and concern, among others, water relations, photosynthesis and carbon metabolism, growth, and mineral nutrients of leaves. The indicators to measure physiological variables in forest monitoring programs must be easy to apply in the field with current state-of-the-art technologies, be replicable, inexpensive, time efficient and regulated by ad hoc protocols. The ultimate purpose is to provide data to feed process-based models to predict mortality and threats in forests due to climate change. This study reviews the problems and perspectives connected to the realization of a systematic assessment of physiological variables and proposes a set of indicators suitable for future application in forest monitoring programs.

Fire‐Induced Carbon Loss and Tree Mortality in Siberian Larch Forests

AbstractClimate change is intensifying the fire regime across Siberia, with the potential to alter carbon combustion and post‐fire carbon re‐accumulation trajectories. Few field‐based estimates of fire severity (e.g., carbon combustion and tree mortality) exist in Siberian larch forests (Larix spp.), which limits our ability to project how an intensified fire regime will affect regional and global climate feedbacks. Here, we present field‐based estimates of fire‐induced tree mortality and carbon loss in eastern Siberian larch forests. Our results suggest that fires in this region result in high tree mortality (means of 83% and 76% at Arctic and subarctic sites, respectively). In both absolute and relative terms, aboveground carbon loss following fire is higher in Siberian larch forests than in North America, but belowground carbon loss is considerably lower. This suggests fundamental differences in wildfire behavior and carbon dynamics between dominant vegetation types across the boreal biome.

Enhanced Drought Exposure Increasingly Threatens More Forests Than Observed

AbstractForest protection and afforestation have been identified as a means to partially offset anthropogenic CO2 emissions. Yet, increasingly frequent observations of drought‐induced tree mortality are reported. Here, we applied a risk analysis framework for global drought‐induced forest mortality by examining extreme reductions in greenness and water content of forest canopies during past mortality events as well as growth recovery of surviving individual trees following stand‐scale mortality events. We defined a drought‐induced mortality risk index (DMR) that explains 80% of documented tree mortality. Rising CO2 alleviated the increase of DMR with short‐term drought, however, the observed DMR increases with long‐term drought no matter whether considering plant responses to CO2. DMR in sites where tree mortality has been observed significantly increased since the 1980s. More than that, drought exposure threatened 0.28 billion hectares of forested areas. Our framework highlights how climate change‐induced drought, especially hotter‐droughts, threatens the sustainability of global forests.

Intensified Structural Overshoot Aggravates Drought Impacts on Dryland Ecosystems

AbstractA favorable environment can induce vegetation overgrowth to exceed the ecosystem carrying capacity, exacerbating water resource depletion and increasing the risk of lagged effects on vegetation degradation. This phenomenon is defined as structural overshoot, which can lead to large‐scale forest mortality and grassland deterioration. However, the current understanding of structural overshoot remains incomplete due to the complex time‐varying interactions between vegetation and climate. Here, we used a dynamic learning algorithm to decompose the contributions of vegetation and climate to drought occurrence, trace the connection between antecedent and concurrent vegetation dynamics, thus effectively capturing structural overshoot. This study focused on the climate‐sensitive hotspot in Northwest China drylands, where significant vegetation greening induced by a warming and wetting climate was detected during 1982–2015, leading to soil moisture deficit and aggravating vegetation degradation risks during droughts. We found that during this period, structural overshoot induced approximately 34.6% of the drought events, and lagged effects accounted for 16.7% of the vegetation degradation for these overshoot drought events. The occurrence of overshoot droughts exhibited an increasing trend over time, which was primarily driven by vegetation overgrowth followed by precipitation variation. Although the severity of overshoot and non‐overshoot droughts were generally comparable in spatial distribution, the impact of overshoot droughts is still becoming increasingly obvious. Our results indicate that the expected intensified overshoot droughts cannot be ignored and emphasize the necessity of sustainable agroecosystem management strategies.

Functionally Assembled Terrestrial Ecosystem Simulator (FATES) for Hurricane Disturbance and Recovery

AbstractTropical cyclones are an important cause of forest disturbance, and major storms caused severe structural damage and elevated tree mortality in coastal tropical forests. Model capabilities that can be used to understand post‐hurricane forest recovery are still limited. We use a vegetation demography model, the Functionally Assembled Terrestrial Ecosystem Simulator, coupled with the Energy Exascale Earth System Model Land Model (ELM‐FATES) to study the processes and the key factors regulating post‐hurricane forest recovery. We implemented hurricane‐induced forest damage, including defoliation, structural biomass reduction, and tree mortality, performed ensemble model simulations, and used random forest feature importance. For the simulation in the Luquillo Experimental Forest, Puerto Rico, we identified factors controlling the post‐hurricane forest recovery, and quantified the sensitivity of key model parameters to the post‐hurricane forest recovery. The results indicate a tendency for the Bisley forests to shift toward the light demanding plant functional type (PFT) when the pre‐hurricane biomass between the light demanding and shade tolerant PFTs is nearly equal and forests experience hurricane disturbance with mortality >60% for both the two PFTs. Under more realistic conditions where the shade tolerant PFT is initially dominant, mortality >80% is required for a shift toward dominance of the light demanding PFT at Bisley. Hurricane mortality and background mortality are the two major factors regulating post‐hurricane forest recovery in simulations. This research improves understanding of the ELM‐FATES model behavior associated with hurricane disturbance and provides guidance for dynamic vegetation model development in representing hurricane induced forest damage with varied intensities.

Impact of drought-induced forest mortality on terrestrial carbon cycle from remote sensing perspective

Impact of drought-induced forest mortality on terrestrial carbon cycle from remote sensing perspective

Bark beetle outbreaks in Picea abies stands are associated with changes in wood-inhabiting fungal communities and seedling establishment on logs

In recent decades bark beetle outbreaks have caused high mortality in natural mountain Picea abies forests in Central Europe. This study evaluated factors affecting seedling establishment of P. abies by focusing on the role of fungal communities in decaying logs, which is an important regeneration microsite. At the control site, which was affected by lower severity disturbance, well decayed logs with moss and vegetation cover hosted many seedlings. At the disturbed site, which experienced high mortality by bark beetles, greater canopy openness suppressed vegetation on logs and lowered seedling density. Additionally, the presence of a white rot basidiomycete Phellopilus nigrolimitatus was positively associated with seedling density. In contrast, the presence of a brown rot basidiomycete Fomitopsis pinicola was negatively associated with seedling density. The relationships between these decomposer fungi and seedling density might be partly attributed to changes in wood chemical properties and associated mycorrhizal and pathogenic fungi.

Influence of drought and minimum temperature on tree growth and water use efficiency of Mediterranean species

The world's forests are currently facing the impacts of climate change and associated extreme events, which are adversely affecting natural ecosystems and increasing risks of forest mortality. In the Mediterranean region, where water is already a limiting factor, drought stress is having a severe impact on tree growth. Different species have developed physiological mechanisms to cope with drought, and an increase in water use efficiency has been observed in several drought-tolerant species. This paper analysed the growth trends and the ecophysiological responses of four widespread Mediterranean species (Pinus pinaster Aiton, Pinus pinea L., Pinus halepensis Mill and Quercus ilex L.) to climate variability, in a natural reserve of the Vesuvio National Park (Southern Italy). Dendrochronological analyses were used to measure tree-ring widths and to estimate basal area increments for each species. Stable isotope analyses of δ13C were performed to calculate intrinsic water use efficiency on an annual scale for the four species. Climate-growth relationships suggested that temperatures, in particular annual minimum temperature, had a significant impact on the growth of each species. The species that showed the highest resistance to hot periods and water scarcity was Pinus halepensis, presenting the highest intrinsic water use efficiency values. On the other hand, Quercus ilex was found to be the most susceptible to prolonged drought periods and sensitive to changes in precipitation, resulting in the weakest growth rates during extreme heat and cold periods. Our study demonstrated the importance of better understanding the ecophysiological responses of each species to develop sound conservation and forest management plans.

A climate-spatial matrix growth model for major tree species in Lesser Khingan Mountains and responses of forest dynamics change to different representative concentration path scenarios

IntroductionClimate change affects forest distribution, species composition, structure, and yield due to the sensitivity of forests to temperature, precipitation, and CO2. Therefore, for forest management decisions regarding climate change, it is crucial to explore the response of forest growth, mortality, and recruitment to future climate. We aimed to establish tree species’ responses by introducing variables such as climate, stand spatial structure parameters, and diversity indices.MethodsWe produced fixed parameter transition matrix model (FM), climate-sensitive matrix growth model (CM) and climate-spatial matrix growth model (SCM) using data from 786 plots collected during the 7th (2010), and 8th (2015), Chinese National Forest Inventories in Heilongjiang Province, and long-term predictive performance of CM, SCM, and FM were compared using same data. The models were compared using tenfold cross-validation and long-term predictive performance analysis. To predict the response of major tree species in the Lesser Khingan Mountains to three future climate change scenarios (RCP2.6, RCP4.5, RCP8.5).Results and discussionThe cross-validation results show small significant differences among the three models for short-term prediction (5 years), with the FM performing slightly better than the CM and the SCM. In contrast, for long-term projections (85 years), SCM outperformed FM and CM under three different RCPs, and SCM and CM under three representative concentration paths (RCPs), i.e., RCP2.6, RCP4.5, and RCP8.5, suggesting that rather different dynamics are more reliable, since climatic factors are taken into account which may significantly affect forest dynamics, while changes in stand spatial structure also affect the sensitivity of trees to climate, especially in long-term prediction interval, the results of this paper may provide a theoretical basis for optimizing forest management strategies under climate change.

Recruitment dynamics in a tropical karst seasonal rain forest: Revealing complex processes from spatial patterns

Spatial patterns can reveal many ecological processes in forest communities; thus, understanding the spatial patterns of trees and their interactions is key to exploring forest dynamics. However, few studies have explored the spatial patterns and interactions between adults and recruits over longer time spans in tropical karst forests. A forest dynamics census was conducted (2011–2021) in a 15-ha karst seasonal rainforest plot at the Nonggang National Nature Reserve, in Guangxi, China. The tree community structure, which included a total of 20 tree species (≥ 50 individuals) at various states of recruitment, survival, and mortality, were selected and investigated via detailed analyses. First, univariate pair correlation functions and bivariate mark correlation functions were utilized to analyze the spatial patterns of dead recruits, surviving recruits, and adults. Aggregation was the dominant intraspecific distribution pattern in the plot that decreased at larger scales, which indicated that dispersal was limited. The segregation of bivariate patterns in most species suggested that there was scramble competition between the surviving and dead recruits, which translated to their not clustering around adults. Second, it was revealed through testing that density dependence was not prevalent. However, negative density dependence was more common in species that exhibited density dependence, as various species respond differently to changes in population density. Third, most recruits had a low probability of survival, which for several dominant species was influenced by neighborhood effects. This study did not support the Janzen-Connell hypothesis, as the survival probability of most recruits was not enhanced with the distance from adults. This meant that the effects of distance from adults on the growth of recruits in Nonggang forests were negligible. These results suggested that dispersal limitations and habitat heterogeneity played more significant roles in the regulation of tree spatial patterns and seedling growth (or mortality) in tropical karst seasonal rain forests. This work will contribute to the restoration and conservation of fragile forest communities in Karst regions, while providing a theoretical basis for biodiversity research, forest management planning, and ecosystem services.

Quantification of hydraulic trait control on plant hydrodynamics and risk of hydraulic failure within a demographic structured vegetation model in a tropical forest (FATES–HYDRO V1.0)

Abstract. Vegetation plays a key role in the global carbon cycle and thus is an important component within Earth system models (ESMs) that project future climate. Many ESMs are adopting methods to resolve plant size and ecosystem disturbance history, using vegetation demographic models. These models make it feasible to conduct more realistic simulation of processes that control vegetation dynamics. Meanwhile, increasing understanding of the processes governing plant water use, and ecosystem responses to drought in particular, has led to the adoption of dynamic plant water transport (i.e., hydrodynamic) schemes within ESMs. However, the extent to which variations in plant hydraulic traits affect both plant water stress and the risk of mortality in trait-diverse tropical forests is understudied. In this study, we report on a sensitivity analysis of an existing hydrodynamic scheme (HYDRO) model that is updated and incorporated into the Functionally Assembled Terrestrial Ecosystem Simulator (FATES) (FATES–HYDRO V1.0). The size- and canopy-structured representation within FATES is able to simulate how plant size and hydraulic traits affect vegetation dynamics and carbon–water fluxes. To better understand this new model system, and its functionality in tropical forest systems in particular, we conducted a global parameter sensitivity analysis at Barro Colorado Island, Panama. We assembled 942 observations of plant hydraulic traits on 306 tropical plant species for stomata, leaves, stems, and roots and determined the best-fit statistical distribution for each trait, which was used in model parameter sampling to assess the parametric sensitivity. We showed that, for simulated leaf water potential and loss of hydraulic conductivity across different plant organs, the four most important traits were associated with xylem conduit taper (buffers increasing hydraulic resistance with tree height), stomatal sensitivity to leaf water potential, maximum stem hydraulic conductivity, and the partitioning of total hydraulic resistance above vs. belowground. Our analysis of individual ensemble members revealed that trees at a high risk of hydraulic failure and potential tree mortality generally have a lower conduit taper, lower maximum xylem conductivity, lower stomatal sensitivity to leaf water potential, and lower resistance to xylem embolism for stem and transporting roots. We expect that our results will provide guidance on future modeling studies using plant hydrodynamic models to predict the forest responses to droughts and future field campaigns that aim to better parameterize plant hydrodynamic models.

An Analysis of the Factors Affecting Forest Mortality and Research on Forecasting Models in Southern China: A Case Study in Zhejiang Province

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.

Prescribed fire lessens bark beetle impacts despite varied effects on fuels 13 years after mastication and fire in a Sierra Nevada mixed-conifer forest

Mastication, thinning, and prescribed fire can help shift fire-prone forests to a structure and composition more resilient to wildfire, but the ability to evaluate treatment effectiveness requires monitoring forest response to disturbances over time after treatment. In this study, we investigated fuel loadings, forest structure, and tree growth to assess treatment legacies thirteen years after mastication, prescribed fire, and surface fuel pull-back from tree boles in Sierra Nevada mixed-conifer forest. An outbreak of bark beetles between 2011 and 2018 impacted all plots but burned treatments had lower overstory mortality relative to unburned treatments which experienced an 80 % decline in live tree biomass. Tree diameter, canopy density, and surface fuel loadings became similar across all treatments during the 13 year time period. Height to live crown remained elevated in burned treatments relative to the control but had lowered by an average of 1.9 ± 0.3 (SE) m across all treatments. Radial tree growth did not have a sustained response to treatment and was greater in burned treatments for only a single year, 2011, several years post-treatment. Prescribed fire decreased duff mass by 56 % relative to unburned treatments but did not affect forest floor bulk density. Downed woody fuel loadings (1-h – 1000-h) were similar across treatments. The invasive Bromus tectorum (cheatgrass) had uniformly high cover across treatments. Whereas treatments were largely ineffective at producing long-term reductions in surface fuel loadings, the enduring reductions in duff loadings and reduced overstory mortality support the long-term utility of prescribed fire. Cumulatively, our results highlight the potential for prescribed fire to reduce overstory mortality and duff loadings in dry mixed-conifer forests, thereby contributing more effectively to fire-resilient characteristics relative to other fuel reduction treatments.

Increased atmospheric moisture demand induced a reduction in the water content of boreal forest during the past three decades

Widespread forest mortality has been observed in recent years which may be related to the forest water content. Changes in atmospheric demand for water (vapour pressure deficit, VPD) and soil moisture due to climate change affect plants in terrestrial ecosystems. Hence, it is crucial to determine the impact of variations in soil-atmosphere water content on forest water content to enhance our predictive capability of future forest dynamics. Here, we explored the dynamics of forest water content in the boreal forest (BFC) based on remote sensing Ku-band vegetation optical depth (VOD) data and found a declining trend from 1988 to 2016. The study revealed a strong negative correlation between VPD and VOD and the negative trend of BFC water content increased with increasing annual VPD. Further analysis found a negative correlation between monthly transpiration and VOD, and a positive correlation between canopy conductance and VOD. The relationship exhibited greater significance in regions characterized by a more rapid increase in VPD suggesting elevated VPD led to a higher transpiration, resulting in a decline in forest water content and subsequent plant physiological regulation. This occurred consistently in intact and managed boreal forest, implying common climatic drivers on a large scale. The decrease of annual mean VOD was slower in the intact boreal forest than in the managed forest, which may be due to the diversity and richness of the intact forest. The findings enhanced the understanding of the dynamics of forest water content under atmospheric drought caused by climate change, which requires the adoption of strategies to prevent forest mortality.

A robust approach and analytical tool for identifying early warning signals of forest mortality

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.

High-resolution data reveal a surge of biomass loss from temperate and Atlantic pine forests, contextualizing the 2022 fire season distinctiveness in France

Abstract. The frequency and intensity of summer droughts and heat waves in Western Europe have been increasing, raising concerns about the emergence of fire hazard in less fire-prone areas. This exposure of old-growth forests hosting unadapted tree species may cause disproportionately large biomass losses compared to those observed in frequently burned Mediterranean ecosystems. Therefore, analyzing fire seasons from the perspective of exposed burned areas alone is insufficient; we must also consider impacts on biomass loss. In this study, we focus on the exceptional 2022 summer fire season in France and use very high-resolution (10 m) satellite data to calculate the burned area, tree height at the national level, and subsequent ecological impact based on biomass loss during fires. Our high-resolution semi-automated detection estimated 42 520 ha of burned area, compared to the 66 393 ha estimated by the European automated remote sensing detection system (EFFIS), including 48 330 ha actually occurring in forests. We show that Mediterranean forests had a lower biomass loss than in previous years, whereas there was a drastic increase in burned area and biomass loss over the Atlantic pine forests and temperate forests. High biomass losses in the Atlantic pine forests were driven by the large burned area (28 600 ha in 2022 vs. 494 ha yr−1 in 2006–2021 period) but mitigated by a low exposed tree biomass mostly located on intensive management areas. Conversely, biomass loss in temperate forests was abnormally high due to both a 15-fold increase in burned area compared to previous years (3300 ha in 2022 vs. 216 ha in the 2006–2021 period) and a high tree biomass of the forests which burned. Overall, the biomass loss (i.e., wood biomass dry weight) was 0.25 Mt in Mediterranean forests and shrublands, 1.74 Mt in the Atlantic pine forest, and 0.57 Mt in temperate forests, amounting to a total loss of 2.553 Mt, equivalent to a 17 % increase of the average natural mortality of all French forests, as reported by the national inventory. A comparison of biomass loss between our estimates and global biomass/burned areas data indicates that higher resolution improves the identification of small fire patches, reduces the commission errors with a more accurate delineation of the perimeter of each fire, and increases the biomass affected. This study paves the way for the development of low-latency, high-accuracy assessment of biomass losses and fire patch contours to deliver a more informative impact-based characterization of each fire year.

Nitrogen addition enhances tree radial growth but weakens its recovery from drought impact in a temperate forest in northern China

Forest growth in the majority of northern China is currently limited by drought and low nitrogen (N) availability. Drought events with increasing intensity have threatened multiple ecosystem services provided by forests. Whether N addition will have a detrimental or beneficial moderation effect on forest resistance and recovery to drought events was unclear. Here, our study focuses on Pinus tabulaeformis, which is the main plantation forest species in northern China. We investigated the role of climate change and N addition in driving multi-year tree growth with an 8-year soil nitrogen fertilization experiment and analyzing 184 tree ring series. A moderate drought event occurred during the experiment, providing an opportunity for us to explore the effects of drought and N addition on tree resistance and recovery. We found that N addition was beneficial for increasing the resistance of middle-aged trees, but had no effect on mature trees. The recovery of trees weakened significantly with increasing N addition, and the reduction in fine root biomass caused by multiyear N addition was a key influencing factor limiting recovery after moderate drought. Our study implies that the combined effect of increasing drought and N deposition might increase the risk of pine forest mortality in northern China.

Source height and contact with terrestrial soil drive transplanted epiphyte performance

Abstract Epiphytes are characterized by their ability to survive without a root connection to the ground, but many basic life‐history traits and ecological trade‐offs of this unique aerial growth habit remain largely uncharacterized. Mortality causes are still not well understood, but falling from the host tree has been suggested as a leading cause of epiphyte mortality and community dynamics. Little empirical evidence exists for why epiphytes do not survive when forced to become terrestrial, and few studies exist that transplant epiphytes between high‐ and low‐forest strata to test trade‐offs between thriving in canopy environments and survival in the forest understorey. Here, we experimentally test two hypotheses regarding the drivers of epiphyte mortality in a cloud forest of central Panama. We test whether simple contact with terrestrial soil is deleterious to epiphytes, preliminarily testing the epiphyte enemy escape hypothesis, and test the vertical niche differentiation hypothesis, wherein epiphytes are specifically adapted for microsites throughout the vertical forest strata. By monitoring survival, leaf loss and health status of 270 transplanted epiphytes for a year and a half, we pinpoint the extent to which soil contact and height of origin regulate epiphyte performance. We found that contact with terrestrial soil itself was detrimental to epiphytes in situ, providing some of the first empirical data to explain why falling onto the ground, versus falling into the understorey, is particularly fatal to epiphytes. However, we also found that mortality rates vary substantially among taxonomic groups and among epiphytes that originally came from different height strata. Synthesis. Plants that are adapted for the canopy experience a trade‐off with higher mortality when in contact with terrestrial soil. Follow‐up studies should explore the role of terrestrial soil microbes and physiological constraints as potential drivers of decreased grounded epiphyte survival.

The Influence of Winter Snowpack on the Use of Summer Rains in Montane Pine Forests Across the Southwest U.S.

AbstractA two decade‐long megadrought, with likely anthropogenic causes, has impacted forest growth and mortality across the southwestern U.S. Given this event, and the future likelihood of similar climate challenges, it is important to understand how different water resources are used by semi‐arid forests in this region. Within the geographic domain of the North American Monsoon climate system, we studied seasonal water‐use in eight different Pinus ponderosa montane forests distributed across a climate gradient with varying contributions from winter and summer precipitation. We collected oxygen isotopes from precipitation, soil, and xylem water during two contrasting hydrologic years to determine how trees differentially use winter versus summer precipitation sources. Most trees switched from using snowmelt water as the primary source during the early‐summer hyper‐arid period, to monsoon rainwater during the late‐summer. However, during the low snowpack year, which represents the most common climate phenomenon during the megadrought, trees at all sites used less summer rain when compared to the higher snowpack year, demonstrating a drought‐induced antecedent influence of winter precipitation on the uptake of summer rain. A possible mechanism to explain the antecedent effect is an earlier snow disappearance during the low snowpack year weakening hydrologic connectivity within the soil profile, decreasing the soil infiltration of summer rains. However, in years with higher snowpack, the snow lasts longer, and this can improve the hydrologic connectivity within the soil profile. As a result, there is more infiltration of summer rains into the soils. This can enhance the maintenance of active shallow fine‐root biomass during the period when snowpack disappears, and monsoon rains have yet to arrive. These findings provide insight into how the seasonal interactions between major seasonal climate systems influence forest tree water use in the face of an extreme megadrought.