Topography-driven microclimate gradients shape forest structure, diversity, and composition in a temperate refugial forest

Macroclimate drives vegetation distributions, but fine-scale topographic variation can generate microclimate refugia for plant persistence in unsuitable areas. However, we lack quantitative descriptions of topography-driven microclimatic variation and how it shapes forest structure, diversity, and composition. We hypothesized that topographic variation and the presence of the forest overstory cause spatiotemporal microclimate variation affecting tree performance, causing forest structure, diversity, and composition to vary with topography and microclimate, and topography and the overstory to buffer microclimate. In a 20.2-ha inventory plot in the North American Great Plains, we censused woody stems ≥1 cm in diameter and collected detailed topographic and microclimatic data. Across 59-m of elevation, microclimate covaried with topography to create a sharp desiccation gradient, and topography and the overstory buffered understory microclimate. The magnitude of microclimatic variation mirrored that of regional-scale variation: with increasing elevation, there was a decrease in soil moisture corresponding to the difference across ~2.1° of longitude along the east-to-west aridity gradient and an increase in air temperature corresponding to the difference across ~2.7° of latitude along the north-to-south gradient. More complex forest structure and higher diversity occurred in moister, less-exposed habitats, and species occupied distinct topographic niches. Our study demonstrates how topographic and microclimatic gradients structure forests in putative climate-change refugia, by revealing ecological processes enabling populations to be maintained during periods of unfavorable macroclimate.

Climate-induced tree-mortality pulses are obscured by broad-scale and long-term greening

Vegetation greening has been suggested to be a dominant trend over recent decades, but severe pulses of tree mortality in forests after droughts and heatwaves have also been extensively reported. These observations raise the question of to what extent the observed severe pulses of tree mortality induced by climate could affect overall vegetation greenness across spatial grains and temporal extents. To address this issue, here we analyse three satellite-based datasets of detrended growing-season normalized difference vegetation index (NDVIGS) with spatial resolutions ranging from 30 m to 8 km for 1,303 field-documented sites experiencing severe drought- or heat-induced tree-mortality events around the globe. We find that severe tree-mortality events have distinctive but localized imprints on vegetation greenness over annual timescales, which are obscured by broad-scale and long-term greening. Specifically, although anomalies in NDVIGS (ΔNDVI) are negative during tree-mortality years, this reduction diminishes at coarser spatial resolutions (that is, 250 m and 8 km). Notably, tree-mortality-induced reductions in NDVIGS (|ΔNDVI|) at 30-m resolution are negatively related to native plant species richness and forest height, whereas topographic heterogeneity is the major factor affecting ΔNDVI differences across various spatial grain sizes. Over time periods of a decade or longer, greening consistently dominates all spatial resolutions. The findings underscore the fundamental importance of spatio-temporal scales for cohesively understanding the effects of climate change on forest productivity and tree mortality under both gradual and abrupt changes.

Topography-mediated light environment regulates intra-specific seasonal and diurnal patterns of photosynthetic plasticity and plant ecophysiological adaptation strategies

Due to substantial topographic variations in the Himalaya, incident solar radiation in the forest canopy is highly unequal. This results in significant environmental differences at finer scales and may lead to considerable differences in photosynthetic productivity in montane forests. Therefore, local-scale ecophysiological investigations, may be more effective and instructive than landscape-level inventories and models. We investigated leaf ecophysiological differences and related adaptations between two Quercus semecarpifolia forests in aspect-mediated, significantly varying light regimes in the same mountain catchment. Seasonal and diurnal rates of photosynthesis (A) were significantly higher in south aspect (S) than the north (N). Although temperature was a key contributor to seasonal fluctuations in photosynthetic physiology, photoperiod significantly determined intraspecific variations in seasonal and diurnal plasticity of leaf ecophysiological traits between the two topography-mediated light environments. The regression model for A as a function of stomatal conductivity (gsw) explained the critical role of gsw in triggering photosynthetic plasticity as an adaptive function against varying environmental stresses due to seasonal solar differences. We also examined, modifications in chlorophyll content between the two light regimes across seasons to determine the chlorophyll adaptation strategy. The N aspect had higher leaf chl a, b, and chl a + b and a lower chl-allocation ratio (a/b) than S, which helped to optimize the required light reception in the photoreaction centers for improved photosynthetic performance. The leaf light response curves for A and gsw were observed against varying incident photosynthetic photon flux densities (0-2000 mol.m2 s-1 PPFD) for both aspects. We found that the same species developed significantly distinct light response strategies and photosynthetic capacities in S than in N for the given magnitudes of PPFD. Such acquired ecophysiological adaptations owing to varying light environments may provide significant clues for understanding the impact of future climate change on Himalayan tree species.

Variability in Tree-ring Width and NDVI Responses to Climate at a Landscape Level

Inter-annual climatically driven growth variability of above-ground biomass compartments (for example, tree stems and foliage) controls the intensity of carbon sequestration into forest ecosystems. However, understanding the differences between the climatic response of stem and foliage at the landscape level is limited. In this study, we examined the climate-growth response of stem and leaf biomass and their relationship for Pinus sylvestris (PISY) and Picea abies (PCAB) in topographically complex landscapes. We used tree-ring width chronologies and time series of the normalized difference vegetation index (NDVI) derived from high-resolution Landsat scenes as proxies for stem and leaf biomass, respectively. We then compared growth variability and climate-growth relationships of both biomass proxies between topographical categories. Our results show that the responses of tree rings to climate differ significantly from those found in NDVI, with the stronger climatic signal observed in tree rings. Topography had distinct but species-specific effects: At moisture-limited PISY stands, stem biomass (tree rings) was strongly topographically driven, and leaf biomass (NDVI) was relatively insensitive to topographic variability. In landscapes close to the climatic optimum of PCAB, the relationship between stem and leaf biomass was weak, and their correlations with climate were often inverse, with no significant effects of topography. Different climatic signals from NDVI and tree rings suggest that the response of canopy and stem growth to climate change might be decoupled. Furthermore, our results hint toward different prioritizations of biomass allocation in trees under stressful conditions which might change allometric relationships between individual tree compartments in the long term.

Can NDVI identify drought refugia for mammals and birds in mesic landscapes?

Refugia within landscapes are increasingly important as climate change intensifies, yet identifying refugia, and how they respond to climatic perturbations remains understudied. We use Normalized Difference Vegetation Index (NDVI) developed during extreme drought to identify drought refugia. We then utilise camera trapping to understand the ecological role and importance of these refugia under fluctuating rainfall conditions. Ground foraging mammals and birds were surveyed annually from 2016 to 2019 whereby 171 remote-sensing cameras were deployed in the southern section of the Grampians, Australia. NDVI values were calculated during Australia's millennium drought, allowing the assessment of how NDVI calculated during extreme drought predicts drought refugia and the response of biodiversity to NDVI under rainfall fluctuations. Site occupancy of bird and mammal assemblages were dependent on NDVI, with areas of high NDVI during drought exhibiting characteristics consistent with refugia. Rainfall pulses increased site occupancy at all sites with colonisation probability initially associated with higher NDVI sites. Extinction probabilities were greatest at low NDVI sites when rainfall declined. Within mesic systems, remotely sensed NDVI can identify areas of the landscape that act as drought refugia enabling landscape management to prioritise species conservation within these areas. The protection and persistence of refugia is crucial in ensuring landscapes and their species communities therein are resilient to a range of climate change scenarios.

Disentangling the Factors That Contribute to the Growth of Betula spp. and Cunninghami lanceolata in China Based on Machine Learning Algorithms

Forests are indispensable materials and spiritual foundations for promoting ecosystem circulation and human survival. Exploring the environmental impact mechanism on individual-tree growth is of great significance. In this study, the effects of biogeoclimate, competition, and topography on the growth of Betula spp. and Cunninghamia lanceolata (Lamb.) Hook., two tree species with high importance value in China, were explored by gradient boosting regression tree (GBRT), k-nearest neighbor (KNN), and random forest (RF) machine learning (ML) algorithms. The results showed that the accuracy of RF was better than KNN, which was better than GBRT. All ML algorithms performed well for future diameter at breast height (DBH) predictions; the Willmott’s indexes of agreement (WIA) of each ML algorithm in predicting the future DBH were all higher than 0.97, and the R2 was higher than 0.98 and 0.90, respectively. The individual tree annual growth rate is mainly affected by the single-tree size, and the external environment can promote or inhibit tree growth. Climate and stand structure variables were relatively more important for tree growth than the topographic factors. Lower temperature and precipitation, higher stand density, and canopy closure were more unfavorable for their growth. In afforestation, the following factors should be considered in order: geographic location, meteorological climate, stand structure, and topography.

The other side of droughts: wet extremes and topography as buffers of negative drought effects in an Amazonian forest

There is a consensus about negative impacts of droughts in Amazonia. Yet, extreme wet episodes, which are becoming as severe and frequent as droughts, are overlooked and their impacts remain poorly understood. Moreover, drought reports are mostly based on forests over a deep water table (DWT), which may be particularly sensitive to dry conditions. Based on demographic responses of 30 abundant tree species over the past two decades, in this study we analyzed the impacts of severe droughts but also of concurrent extreme wet periods, and how topographic affiliation (to shallow - SWTs - or deep - DWTs - water tables), together with species functional traits, mediated climate effects on trees. Dry and wet extremes decreased growth and increased tree mortality, but interactions of these climatic anomalies had the highest and most positive impact, mitigating the simple negative effects. Despite being more drought-tolerant, species in DWT forests were more negatively affected than hydraulically vulnerable species in SWT forests. Interaction of wet-dry extremes and SWT depth modulated tree responses to climate, providing buffers to droughts in Amazonia. As extreme wet periods are projected to increase and at least 36% of the Amazon comprises SWT forests, our results highlight the importance of considering these factors in order to improve our knowledge about forest resilience to climate change.

Climate change causes critical transitions and irreversible alterations of mountain forests

Mountain forests are at particular risk of climate change impacts due to their temperature limitation and high exposure to warming. At the same time, their complex topography may help to buffer the effects of climate change and create climate refugia. Whether climate change can lead to critical transitions of mountain forest ecosystems and whether such transitions are reversible remain incompletely understood. We investigated the resilience of forest composition and size structure to climate change, focusing on a mountain forest landscape in the Eastern Alps. Using the individual-based forest landscape model iLand, we simulated ecosystem responses to a wide range of climatic changes (up to a 6°C increase in mean annual temperature and a 30% reduction in mean annual precipitation), testing for tipping points in vegetation size structure and composition under different topography scenarios. We found that at warming levels above +2°C a threshold was crossed, with the system tipping into an alternative state. The system shifted from a conifer-dominated landscape characterized by large trees to a landscape dominated by smaller, predominantly broadleaved trees. Topographic complexity moderated climate change impacts, smoothing and delaying the transitions between alternative vegetation states. We subsequently reversed the simulated climate forcing to assess the ability of the landscape to recover from climate change impacts. The forest landscape showed hysteresis, particularly in scenarios with lower precipitation. At the same mean annual temperature, equilibrium vegetation size structure and species composition differed between warming and cooling trajectories. Here we show that even moderate warming corresponding to current policy targets could result in critical transitions of forest ecosystems and highlight the importance of topographic complexity as a buffering agent. Furthermore, our results show that overshooting ambitious climate mitigation targets could be dangerous, as ecological impacts can be irreversible at millennial time scales once a tipping point has been crossed.

Integration of Multi-Sensor Data to Estimate Plot-Level Stem Volume Using Machine Learning Algorithms–Case Study of Evergreen Conifer Planted Forests in Japan

The development of new methods for estimating precise forest structure parameters is essential for the quantitative evaluation of forest resources. Conventional use of satellite image data, increasing use of terrestrial laser scanning (TLS), and emerging trends in the use of unmanned aerial systems (UASs) highlight the importance of modern technologies in the realm of forest observation. Each technology has different advantages, and this work seeks to incorporate multiple satellite, TLS- and UAS-based remote sensing data sets to improve the ability to estimate forest structure parameters. In this paper, two regression analysis approaches are considered for the estimation: random forest regression (RFR) and support vector regression (SVR). To collect the dependent variable, in situ measurements of individual tree parameters (tree height and diameter at breast height (DBH)) were taken in a Japanese cypress forest using the nondestructive TLS method, which scans the forest to obtain dense and accurate point clouds under the tree canopy. Based on the TLS data, the stem volume was then computed and treated as ground truth information. Topographic and UAS information was then used to calculate various remotely sensed explanatory variables, such as canopy size, canopy cover, and tree height. Canopy cover and canopy shapes were computed via the orthoimages derived from the UAS and watershed segmentation method, respectively. Tree height was computed by combining the digital surface model (DSM) from the UAS and the digital terrain model (DTM) from the TLS data. Topographic variables were computed from the DTM. The backscattering intensity in the satellite imagery was obtained based on L-band (Advanced Land Observing Satellite-2 (ALOS-2) Phased Array type L-band Synthetic Aperture Radar-2 (PALSAR-2)) and C-band (Sentinel-1) synthetic aperture radar (SAR). All satellite (10–25 m resolution), TLS (3.4 mm resolution) and UAS (2.3–4.6 cm resolution) data were then combined, and RFR and SVR were trained; the resulting predictive powers were then compared. The RFR method yielded fitting R2 up to 0.665 and RMSE up to 66.87 m3/ha (rRMSE = 11.95%) depending on the input variables (best result with canopy height, canopy size, canopy cover, and Sentinel-1 data), and the SVR method showed fitting R2 up to 0.519 and RMSE up to 80.12 m3/ha (rRMSE = 12.67%). The RFR outperformed the SVR method, which could delineate the relationship between the variables for better model accuracy. This work has demonstrated that incorporating various remote sensing data to satellite data, especially adding finer resolution data, can provide good estimates of forest parameters at a plot level (10 by 10 m), potentially allowing advancements in precision forestry.

Relationship between heatwave-induced forest die-off and climatic suitability in multiple tree species

In recent decades, many forest die-off events have been reported in relation to climate-change-induced episodes, such as droughts and heat waves. To understand how these extreme climatic events induce forest die-off, it is important to find a tool to standardize the climatic conditions experienced by different populations during a specific climatic event, taking into account the historic climatic conditions of the site where these populations live (bioclimatic niche). In this study, we used estimates of climatic suitability calculated from species distribution models (SDMs) for such purpose. We studied forest die-off across France during the 2003 heatwave that affected Western Europe, using 2,943 forest inventory plots dominated by 14 single tree species. Die-off severity was estimated by Normalized Difference Vegetation Index (NDVI) loss using Moderate-resolution Imaging Spectroradiometer remote sensor imagery. Climatic suitability at the local level during the historical 1979-2002 period (HCS), the episode time (2003; ECS) and suitability deviance during the historical period (HCS-SD) were calculated for each species by means of boosted regression tree models using the CHELSA climate database and occurrences extracted from European forest inventories. Low HCS-SD and high mean annual temperature explained the overall regional pattern of vulnerability to die-off across different monospecific forests. The combination of high historical and low episode climatic suitability also contributed significantly to overall forest die-off. Furthermore, we observed different species-specific relationships between die-off vulnerability and climatic suitability: Sub-Mediterranean and Mediterranean species tended to be vulnerable in historically more suitable localities (high HCS), whereas Euro-Siberian species presented greater vulnerability when the hot drought episode was more intense. We demonstrated that at regional scale, past climatic legacy plays an important role in explaining NDVI loss during the episode. Moreover, we demonstrated that SDMs-derived indexes, such as HCS, ECS and HCS-SD, could constitute a tool for standardizing the ways that populations and species experience climatic variability across time and space.

Assessment of the Biomass Productivity Decline in the Lower Mekong Basin

This study aimed to delineate the geographic hotspots of negative trends in biomass productivity in the Lower Mekong Basin countries (Vietnam, Cambodia, Laos, and Thailand) and identify correlated regional environmental and anthropogenic factors. A long-term time-series (1982–2015) of Normalized Difference Vegetation Index at a resolution of approximately 9.16 km × 9.16 km was used to specify the areas with significant decline or increase in productivity. The relationships between vegetation changes and land attributes, such as climate, population density, soil/terrain conditions, and land-cover types, were examined. Rainfall time-series maps were used to identify areas that might have been affected by land degradation from those correlated with rainfall. Most of the detected potentially degraded areas were found in Cambodia, the Northwest and the Highland of Vietnam, the Northern Mountains of Thailand and Laos, and the mountainous border between Laos, Vietnam, and Cambodia. About 15% of the total land area of these four countries experienced a reduction in biomass productivity during the 34-year study period. The map of hotspots of changes in productivity can be used to direct further studies, including those at finer spatial resolution that may support policy makers and researchers in targeting the strategies for combating land degradation.

Modelling the Effect of Microsite Influences on the Growth and Survival of Juvenile Eucalyptus globoidea (Blakely) and Eucalyptus bosistoana (F. Muell) in New Zealand

The effect of microsite on juvenile forest plantation yield is rarely explored. This is because juvenile plantation growth is considered to be reasonably homogenous due to a lack of resource competition between trees prior to canopy closure. However, models of juvenile plantation height growth and survival that are sensitive to microsite variation could aid decisions relating to site preparation, plantation establishment and early silvicultural treatments. In this study, juvenile Eucalyptus bosistoana and E. globoidea height growth and survival proportion were modelled against topographic and environmental microsite characteristics as independent variables. The experiment included three different sites situated in a sub-humid region of New Zealand. A total of 540 plots were planted with 18,540 trees in regular rows and columns. Micro-topographical variables significantly influenced height growth and survival proportion of both E. bosistoana and E. globoidea, but species differed in their responses. More sheltered microsites yielded greater height growth and survival for both species. The height of both species was influenced by wind exposure, morphometric protection, and distance from the nearest ridge. E. bosistoana height was also influenced by topographic position and surface plan curvature. Survival was affected by surface profile curvature for both species, while E. globoidea survival was also impacted by surface plan curvature and distance from the top ridge. This study identified microsite factors influencing juvenile height and survival of two Eucalyptus species.

Refining predictions of population decline at species' rear edges

According to broad-scale application of biogeographical theory, widespread retractions of species' rear edges should be seen in response to ongoing climate change. This prediction rests on the assumption that rear edge populations are "marginal" since they occur at the limit of the species' ecological tolerance and are expected to decline in performance as climate warming pushes them to extirpation. However, conflicts between observations and predictions are increasingly accumulating and little progress has been made in explaining this disparity. We argue that a revision of the concept of marginality is necessary, together with explicit testing of population decline, which is increasingly possible as data availability improves. Such action should be based on taking the population perspective across a species' rear edge, encompassing the ecological, geographical and genetic dimensions of marginality. Refining our understanding of rear edge populations is essential to advance our ability to monitor, predict and plan for the impacts of environmental change on species range dynamics.

Landscape Topoedaphic Features Create Refugia from Drought and Insect Disturbance in a Lodgepole and Whitebark Pine Forest

Droughts and insect outbreaks are primary disturbance processes linking climate change to tree mortality in western North America. Refugia from these disturbances—locations where impacts are less severe relative to the surrounding landscape—may be priorities for conservation, restoration, and monitoring. In this study, hypotheses concerning physical and biological processes supporting refugia were investigated by modelling the landscape controls on disturbance refugia that were identified using remotely sensed vegetation indicators. Refugia were identified at 30-m resolution using anomalies of Landsat-derived Normalized Difference Moisture Index in lodgepole and whitebark pine forests in southern Oregon, USA, in 2001 (a single-year drought with no insect outbreak) and 2009 (during a multi-year drought and severe outbreak of mountain pine beetle). Landscape controls on refugia (topographic, soil, and forest characteristics) were modeled using boosted regression trees. Landscape characteristics better explained and predicted refugia locations in 2009, when forest impacts were greater, than in 2001. Refugia in lodgepole and whitebark pine forests were generally associated with topographically shaded slopes, convergent environments such as valleys, areas of relatively low soil bulk density, and in thinner forest stands. In whitebark pine forest, refugia were associated with riparian areas along headwater streams. Spatial patterns in evapotranspiration, snowmelt dynamics, soil water storage, and drought-tolerance and insect-resistance abilities may help create refugia from drought and mountain pine beetle. Identification of the landscape characteristics supporting refugia can help forest managers target conservation resources in an era of climate-change exacerbation of droughts and insect outbreaks.

Accounting for landscape heterogeneity improves spatial predictions of tree vulnerability to drought

As climate change continues, forest vulnerability to droughts and heatwaves is increasing, but vulnerability varies regionally and locally through landscape position. Also, most models used in forecasting forest responses to heat and drought do not incorporate relevant spatial processes. In order to improve spatial predictions of tree vulnerability, we employed a nonlinear stochastic model of soil moisture dynamics accounting for landscape differences in aspect, topography and soils. Across a watershed in central Texas we modeled dynamic water stress for a dominant tree species, Juniperus ashei, and projected future dynamic water stress through the 21^st century. Modeled dynamic water stress tracked spatial patterns of remotely sensed drought-induced canopy loss. Accuracy in predicting drought-impacted stands increased from 60%, accounting for spatially variable soil conditions, to 72% when also including lateral redistribution of water and radiation/temperature effects attributable to aspect. Our analysis also suggests that dynamic water stress will increase through the 21^st century, with trees persisting at only selected microsites. Favorable microsites/refugia may exist across a landscape where trees can persist; however, if future droughts are too severe, the buffering capacity of an heterogeneous landscape could be overwhelmed. Incorporating spatial data will improve projections of future tree water stress and identification of potential resilient refugia.

Summer dry-down modulates the isotopic composition of soil CO2 production in snow-dominated landscapes

In mountainous landscapes, soil moisture is highly dynamic due to the effects of topography and the temporal variability imposed by seasonal precipitation, including rainfall and snow. Soil moisture is known to affect ecosystem carbon exchange both aboveground and belowground, as well as the stable isotopic composition of exchanged CO₂. In this study we used an extensive suite of measurements to examine the effects of seasonal changes in soil moisture on the isotopic composition of soil CO₂ production at the landscape level. We show that the seasonal decline in soil moisture (i.e., summer dry-down) appeared to impose a trend in the δ¹³C of soil CO₂ production (δ_P) with more negative δ_P early in the growing season when soils were wet, and more positive δ_P as the growing season progressed and soils dried out. This seemingly generalizable pattern for a snow-dominated watershed is likely to represent the variability of recently assimilated C, tracked through the plant-soil system and imprinted in the respired CO₂. Thus, our observations suggest that, at least for mountainous environments, seasonal changes in δ_P are largely mediated by soil moisture and their spatial variability is partially organized by topography.

Single-provenance mature conifers show higher non-structural carbohydrate storage and reduced growth in a drier location

Since growth is more sensitive to drought than photosynthesis, trees inhabiting dry regions are expected to exhibit higher carbohydrate storage and less growth than their conspecifics from more humid regions. However, the same pattern can be the result of different genotypes inhabiting contrasting humidity conditions. To test if reduced growth and high carbohydrate storage are environmentally driven by drought, we examined the growth and non-structural carbohydrate (NSC) concentrations in single-provenance stands of mature trees of Pinus contorta Douglas and Pinus ponderosa Douglas ex C. Lawson planted at contrasting humidity conditions (900 versus 300 mm of annual precipitation) in Patagonia, Chile. Individual tree growth was measured for each species and at each location as mean basal area increment of the last 10 years (BAI10), annual shoot elongation for the period 2011-14, and needle length for 2013 and 2014 cohorts. Additionally, needle, branch, stem sapwood and roots were collected from each sampled tree to determine soluble sugars, starch and total NSC concentrations. The two species showed lower mean BAI10 and 2013 needle length in the dry site; P. ponderosa also had lower annual shoot extension for 2011 and 2014, and lower 2014 needle length, in the dry than in the mesic site. By contrast, NSC concentrations of all woody tissues for both species were either similar or higher in the dry site when compared with the mesic site. Patterns of starch and sugars were substantially different: starch concentrations were similar between sites except for roots of P. ponderosa, which were higher in the dry site, while sugar concentrations of all woody tissues in both species were higher in the dry site. Overall, our study provides evidence that reduced growth along with carbon (C) accumulation is an environmentally driven response to drought. Furthermore, the significant accumulation of low-molecular weight sugars in the dry site is compatible with a prioritized C allocation for osmoregulation. However, since this accumulation did not come at the expense of reduced starch, it is unlikely that growth was limited by C supply in the dry site.

Plant hydraulics improves and topography mediates prediction of aspen mortality in southwestern USA

Elevated forest mortality has been attributed to climate change-induced droughts, but prediction of spatial mortality patterns remains challenging. We evaluated whether introducing plant hydraulics and topographic convergence-induced soil moisture variation to land surface models (LSM) can help explain spatial patterns of mortality. A scheme predicting plant hydraulic safety loss from soil moisture was developed using field measurements and a plant physiology-hydraulics model, TREES. The scheme was upscaled to Populus tremuloides forests across Colorado, USA, using LSM-modeled and topography-mediated soil moisture, respectively. The spatial patterns of hydraulic safety loss were compared against aerial surveyed mortality. Incorporating hydraulic safety loss raised the explanatory power of mortality by 40% compared to LSM-modeled soil moisture. Topographic convergence was mostly influential in suppressing mortality in low and concave areas, explaining an additional 10% of the variations in mortality for those regions. Plant hydraulics integrated water stress along the soil-plant continuum and was more closely tied to plant physiological response to drought. In addition to the well-recognized topo-climate influence due to elevation and aspect, we found evidence that topographic convergence mediates tree mortality in certain parts of the landscape that are low and convergent, likely through influences on plant-available water.