Living on the edge: modeling climate change impacts on sub-humid forests growing in semi-arid environments = Vivint al límit: modelant els impactes del canvi climàtic sobre els boscos semi-humits creixent en entorns semi-àrids

[eng] Semi-arid environments are zones where annual precipitation is less than a half of annual potential evapotranspiration, yet water availability is high enough to allow tree growth. Climate change is expected to have a major impact on forests growing at those regions. Rising atmospheric [CO2] (Ca) is expected to increase forest productivity. However, this fertilizing effect may be partially offset by an increase in water stress, either by reductions in water availability or by increases in atmospheric evaporative demand. Additionally, species-specific responses to climate change may further promote invasive tree species expansion. GOTILWA+ process-based model was used to project the performance of sub-humid forests growing in semi-arid conditions under climate change. However, a carpenter is just as good as the least sharpened of his tools. So, firstly it was developed and tested the RheaG Weather Generator Algorithm, a first-order Markov transition matrix-based WGA, in order to assure the ability to generate statistically robust meteorological time-series. Then, Bayesian inverse modeling was applied in order to calibrate GOTILWA+ model from “in situ” observations from two different forest stands, both occupied by water-demanding tree species growing surrounded by semi-arid conditions. Firstly, combined effects of increased vapor pressure deficit (D), increased Ca and decreased water availability in an S.W. Australian Eucalyptus salinga Sm. plantation were evaluated. Increasing Ca up to 700 ppm alone was projected to increase E. saligna productivity up to a 33%, and forest carbon stock up to a ~60%. However, combined reductions in water availability and D increases offset part of this fertilizing effect, down to 13% and 35%, respectively. Furthermore, limitations on forest productivity due to D increases were projected to occur in a magnitude similar than productivity reductions due to reduced soil water availability. Afterwards, in a N.E. Iberian Mediterranean riparian forest where black locust (Robinia pseudoacacia L.) is outcompeting three autochthonous deciduous tree species, sap flow observations were used to calibrate GOTILWA+ model for black locust and European Ash tree (Fraxinus excelsior L.). Field observations suggested that black locust success was explained by its facultative phreatophytic behavior, as well as an increased water use efficiency in stem growth, when compared with co-occurring autochthonous tree species. GOTILWA+ projections, including regionalized climate change scenarios, suggested that under global warming black locust productivity and growth would be further enhanced than its native counterpart, the European ash. The reasons are an increase on daily productivity as Ca increases, and an enlargement of its vegetative period as temperature rises. As conclusions, the invasive black locust growth performance is expected to be favored by global warming in Mediterranean riparian forests. On the other hand, E. saligna responses to climate change will strongly depend on the balance between the beneficial effects of increasing Ca and physiological limitations due to water stress increase. At stand level, results highlight the importance of accounting for the water available for the trees at the whole soil column, and not only at the superficial soil layers, a challenging issue that is often not resolved in simulation models. Moreover, results also highlight that properly accounting for vapor pressure deficit changes is of a major importance when projecting forest responses to climate change, as it will strongly determine stand changes in productivity and water use efficiency. This thesis also highlights the importance of training simulation models from field observations, not only to describe ecophysiological processes, but also to obtain the most likely set of parameters providing "in situ" observations

Dying by drying: Timing of physiological stress thresholds related to tree death is not significantly altered by highly elevated CO2_{2}

Drought‐induced tree mortality is expected to occur more frequently under predicted climate change. However, the extent of a possibly mitigating effect of simultaneously rising atmospheric [CO$_{2}$] on stress thresholds leading to tree death is not fully understood, yet. Here, we studied the drought response, the time until critical stress thresholds were reached and mortality occurrence of Pinus halepensis (Miller). In order to observe a large potential benefit from eCO$_{2}$, the seedlings were grown with ample of water and nutrient supply under either highly elevated [CO$_{2}$] (eCO$_{2}$, c. 936 ppm) or ambient (aCO$_{2}$, c. 407 ppm) during 2 years. The subsequent exposure to a fast or a slow lethal drought was monitored using whole‐tree gas exchange chambers, measured leaf water potential and non‐structural carbohydrates. Using logistic regressions to derive probabilities for physiological parameters to reach critical drought stress thresholds, indicated a longer period for halving needle starch storage under eCO$_{2}$ than aCO$_{2}$. Stomatal closure, turgor loss, the duration until the daily tree C balance turned negative, leaf water potential at thresholds and time‐of‐death were unaffected by eCO$_{2}$. Overall, our study provides for the first‐time insights into the chronological interplay of physiological drought thresholds under long‐term acclimation to elevated [CO$_{2}$]

Relationships between xylem embolism and tree functioning during drought, recovery, and recurring drought in Aleppo pine

Recent findings suggest that trees can survive high levels of drought-induced xylem embolism. In many cases, the embolism is irreversible and, therefore, can potentially affect post-drought recovery and tree function under recurring droughts. We examined the development of embolism in potted Aleppo pines, a common species in hot, dry Mediterranean habitats. We asked (1) how post-drought recovery is affected by different levels of embolism and (2) what consequences this drought-induced damage has under a recurring drought scenario. Young trees were dehydrated to target water potential (Ψx) values of −3.5, −5.2 and −9.5 MPa (which corresponded to ~6%, ~41% and ~76% embolism), and recovery of the surviving trees was measured over an 8-months period (i.e., embolism, leaf gas-exchange, Ψx). An additional group of trees was exposed to Ψx of −6.0 MPa, either with or without preceding drought (Ψx of −5.2 MPa) to test the effect of hydraulic damage during repeated drought. Trees that reached −9.5 MPa died, but none from the other groups. Embolism levels in dying trees were on average 76% of conductive xylem and no tree was dying below 62% embolism. Stomatal recovery was negatively proportional to the level of hydraulic damage sustained during drought, for at least a month after drought relief. Trees that experienced drought for the second time took longer to reach fatal Ψx levels than first-time dehydrating trees. Decreased stomatal conductance following drought can be seen as “drought legacy,” impeding recovery of tree functioning, but also as a safety mechanism during a consecutive drought

Better safe than sorry: Non-stomatal mechanisms delay drought stress and hydraulic failure in Scots pine saplings

Background/Question/Methods There is no more vital connection than the tight linkage between water and organic carbon, and there is no more paradigmatic example for that than plant photosynthesis. In plants, carbon uptake is done at elevated expenses in terms of water transport from soil to the atmosphere. Under limited water supply, transpiration increases the tension of the within-tree water column. This will eventually lead to emboli formation and loss of hydraulic conductivity, and may result in tree death. The main mechanism by which trees slow down such tension increases is by actively closing their stomata. However, even if stomata are fully closed, some water loss can still occur through cuticular evaporation. Therefore, non-stomatal mechanisms exist that additionally reduce water losses, and hence increase hydraulic safety. Among these, leaf shedding as well as non-stomatal limitations over photosynthesis (NSL, combining increases in mesophyll conductance and biochemical down-regulation on photosynthesis), are well-known but poorly quantified mechanisms that trees may trigger to save water under drought stress. In order to better describe such mechanisms quantitatively, we conducted a severe two-month-long dry-down experiment on potted Scots pine (Pinus sylvestris L.) saplings (n = 6) and under controlled conditions. We measured tree transpiration, photosynthesis and leaf shedding. Based on our observations we trained a state-of-the-art tree hydraulic model and we quantified the impact of the above-mentioned processes on whole-tree percent loss of conductance. Results/Conclusions We found that NSL play a key role in tree drought response by further reducing conductance, which subsequently reduces transpiration and delays dehydration. If sap flow was reduced below a given threshold, saplings responded by shedding leaves. Noteworthy, this threshold was uncorrelated to soil water content. Leaf shedding buffered reductions in xylem water potential and loss of whole-tree conductance in the mid-term. This indicates a hierarchy of active acclimation processes involving a continuous NSL response, and a threshold-based leaf area reduction when P. sylvestris is in danger to lose water to dangerous degrees without any counterpart in form of photosynthetic gain. Combined, both mechanisms reduce whole-plant C uptake, but contribute to tree survival under drought stress

Anatomical adjustments of the tree hydraulic pathway decrease canopy conductance under long-term elevated CO2_2

The cause of reduced leaf-level transpiration under elevated CO$_2$ remains largely elusive. Here, we assessed stomatal, hydraulic, and morphological adjustments in a long-term experiment on Aleppo pine (Pinus halepensis) seedlings germinated and grown for 22–40 months under elevated (eCO$_2$; c. 860 ppm) or ambient (aCO$_2$; c. 410 ppm) CO$_2$. We assessed if eCO$_2$-triggered reductions in canopy conductance (g$_c$) alter the response to soil or atmospheric drought and are reversible or lasting due to anatomical adjustments by exposing eCO$_2$ seedlings to decreasing [CO$_2$]. To quantify underlying mechanisms, we analyzed leaf abscisic acid (ABA) level, stomatal and leaf morphology, xylem structure, hydraulic efficiency, and hydraulic safety. Effects of eCO$_2$ manifested in a strong reduction in leaf-level g$_c$ (−55%) not caused by ABA and not reversible under low CO$_2$ (c. 200 ppm). Stomatal development and size were unchanged, while stomatal density increased (+18%). An increased vein-to-epidermis distance (+65%) suggested a larger leaf resistance to water flow. This was supported by anatomical adjustments of branch xylem having smaller conduits (−8%) and lower conduit lumen fraction (−11%), which resulted in a lower specific conductivity (−19%) and leaf-specific conductivity (−34%). These adaptations to CO$_2$ did not change stomatal sensitivity to soil or atmospheric drought, consistent with similar xylem safety thresholds. In summary, we found reductions of g$_c$ under elevated CO$_2$ to be reflected in anatomical adjustments and decreases in hydraulic conductivity. As these water savings were largely annulled by increases in leaf biomass, we do not expect alleviation of drought stress in a high CO$_2$ atmosphere

Leaf Shedding and Non-Stomatal Limitations of Photosynthesis Mitigate Hydraulic Conductance Losses in Scots Pine Saplings During Severe Drought Stress

During drought, trees reduce water loss and hydraulic failure by closing their stomata, which also limits photosynthesis. Under severe drought stress, other acclimation mechanisms are trigged to further reduce transpiration to prevent irreversible conductance loss. Here, we investigate two of them: the reversible impacts on the photosynthetic apparatus, lumped as non-stomatal limitations (NSL) of photosynthesis, and the irreversible effect of premature leaf shedding. We integrate NSL and leaf shedding with a state-of-the-art tree hydraulic simulation model (SOX+) and parameterize them with example field measurements to demonstrate the stress-mitigating impact of these processes. We measured xylem vulnerability, transpiration, and leaf litter fall dynamics in Pinus sylvestris (L.) saplings grown for 54 days under severe dry-down. The observations showed that, once transpiration stopped, the rate of leaf shedding strongly increased until about 30% of leaf area was lost on average. We trained the SOX+ model with the observations and simulated changes in root-to-canopy conductance with and without including NSL and leaf shedding. Accounting for NSL improved model representation of transpiration, while model projections about root-to-canopy conductance loss were reduced by an overall 6%. Together, NSL and observed leaf shedding reduced projected losses in conductance by about 13%. In summary, the results highlight the importance of other than purely stomatal conductance-driven adjustments of drought resistance in Scots pine. Accounting for acclimation responses to drought, such as morphological (leaf shedding) and physiological (NSL) adjustments, has the potential to improve tree hydraulic simulation models, particularly when applied in predicting drought-induced tree mortality

Assessing model performance via the most limiting environmental driver in two differently stressed pine stands

Climate change will impact forest productivity worldwide. Forecasting the magnitude of such impact, with multiple environmental stressors changing simultaneously, is only possible with the help of process-based models. In order to assess their performance, such models require careful evaluation against measurements. However, direct comparison of model outputs against observational data is often not reliable, as models may provide the right answers due to the wrong reasons. This would severely hinder forecasting abilities under unprecedented climate conditions. Here, we present a methodology for model assessment, which supplements the traditional output-to-observation model validation. It evaluates model performance through its ability to reproduce observed seasonal changes of the most limiting environmental driver (MLED) for a given process, here daily gross primary productivity (GPP). We analyzed seasonal changes of the MLED for GPP in two contrasting pine forests, the Mediterranean Pinus halepensis Mill. Yatir (Israel) and the boreal Pinus sylvestris L. Hyytiala (Finland) from three years of eddy-covariance flux data. Then, we simulated the same period with a state-of-the-art process-based simulation model (LandscapeDNDC). Finally, we assessed if the model was able to reproduce both GPP observations and MLED seasonality. We found that the model reproduced the seasonality of GPP in both stands, but it was slightly overestimated without site-specific fine-tuning. Interestingly, although LandscapeDNDC properly captured the main MLED in Hyytiala (temperature) and in Yatir (soil water availability), it failed to reproduce high-temperature and high-vapor pressure limitations of GPP in Yatir during spring and summer. We deduced that the most likely reason for this divergence is an incomplete description of stomatal behavior. In summary, this study validates the MLED approach as a model evaluation tool, and opens up new possibilities for model improvement.Peer reviewe

Increasing aridity will not offset CO2_{2} fertilization in fast-growing eucalypts with access to deep soil water

Rising atmospheric [CO$_{2}$] (C$_{a}$) generally enhances tree growth if nutrients are not limiting. However, reduced water availability and elevated evaporative demand may offset such fertilization. Trees with access to deep soil water may be able to mitigate such stresses and respond more positively to C$_{a}$. Here, we sought to evaluate how increased vapor pressure deficit and reduced precipitation are likely to modify the impact of elevated C$_{a}$ (eC$_{a}$) on tree productivity in an Australian Eucalyptus saligna Sm. plantation with access to deep soil water. We parameterized a forest growth simulation model (GOTILWA+) using data from two field experiments on E. saligna: a 2‐year whole‐tree chamber experiment with factorial C$_{a}$ (ambient =380, elevated =620 μmol mol$^{-1}$) and watering treatments, and a 10‐year stand‐scale irrigation experiment. Model evaluation showed that GOTILWA+ can capture the responses of canopy C uptake to (1) rising vapor pressure deficit (D) under both C$_{a}$ treatments; (2) alterations in tree water uptake from shallow and deep soil layers during soil dry‐down; and (3) the impact of irrigation on tree growth. Simulations suggest that increasing C$_{a}$ up to 700 μmol mol$^{-1}$ alone would result in a 33% increase in annual gross primary production (GPP) and a 62% increase in biomass over 10 years. However, a combined 48% increase in D and a 20% reduction in precipitation would halve these values. Our simulations identify high D conditions as a key limiting factor for GPP. They also suggest that rising Ca will compensate for increasing aridity limitations in E. saligna trees with access to deep soil water under non‐nutrient limiting conditions, thereby reducing the negative impacts of global warming upon this eucalypt species. Simulation models not accounting for water sources available to deep‐rooting trees are likely to overestimate aridity impacts on forest productivity and C stocks

MEDFATE 2.9.3: a trait-enabled model to simulate Mediterranean forest function and dynamics at regional scales

Regional-level applications of dynamic vegetation models are challenging because they need to accommodate the variation in plant functional diversity, which requires moving away from broadly defined functional types. Different approaches have been adopted in the last years to incorporate a trait-based perspective into modeling exercises. A common parametrization strategy involves using trait data to represent functional variation between individuals while discarding taxonomic identity. However, this strategy ignores the phylogenetic signal of trait variation and cannot be employed when predictions for specific taxa are needed, such as in applications to inform forest management planning. An alternative strategy involves adapting the taxonomic resolution of model entities to that of the data source employed for large-scale initialization and estimating functional parameters from available plant trait databases, adopting diverse solutions for missing data and non-observable parameters. Here we report the advantages and limitations of this second strategy according to our experience in the development of MEDFATE (version 2.9.3), a novel cohort-based and trait-enabled model of forest dynamics, for its application over a region in the western Mediterranean Basin. First, 217 taxonomic entities were defined according to woody species codes of the Spanish National Forest Inventory. While forest inventory records were used to obtain some empirical parameter estimates, a large proportion of physiological, morphological, and anatomical parameters were matched to measured plant traits, with estimates extracted from multiple databases and averaged at the required taxonomic level. Estimates for non-observable key parameters were obtained using meta-modeling and calibration exercises. Missing values were addressed using imputation procedures based on trait covariation, taxonomic averages or both. The model properly simulated observed historical changes in basal area, with a performance similar to an empirical model trained for the same region. While strong efforts are still required to parameterize trait-enabled models for multiple taxa, and to incorporate intra-specific trait variability, estimation procedures such as those presented here can be progressively refined, transferred to other regions or models and iterated following data source changes by employing automated workflows. We advocate for the adoption of trait-enabled and population-structured models for regional-level projections of forest function and dynamics

Tree mortality submodels drive simulated long-term forest dynamics: assessing 15 models from the stand to global scale

Models are pivotal for assessing future forest dynamics under the impacts of changing climate and management practices, incorporating representations of tree growth, mortality, and regeneration. Quantitative studies on the importance of mortality submodels are scarce. We evaluated 15 dynamic vegetation models (DVMs) regarding their sensitivity to different formulations of tree mortality under different degrees of climate change. The set of models comprised eight DVMs at the stand scale, three at the landscape scale, and four typically applied at the continental to global scale. Some incorporate empirically derived mortality models, and others are based on experimental data, whereas still others are based on theoretical reasoning. Each DVM was run with at least two alternative mortality submodels. Model behavior was evaluated against empirical time series data, and then, the models were subjected to different scenarios of climate change. Most DVMs matched empirical data quite well, irrespective of the mortality submodel that was used. However, mortality submodels that performed in a very similar manner against past data often led to sharply different trajectories of forest dynamics under future climate change. Most DVMs featured high sensitivity to the mortality submodel, with deviations of basal area and stem numbers on the order of 10–40% per century under current climate and 20–170% under climate change. The sensitivity of a given DVM to scenarios of climate change, however, was typically lower by a factor of two to three. We conclude that (1) mortality is one of the most uncertain processes when it comes to assessing forest response to climate change, and (2) more data and a better process understanding of tree mortality are needed to improve the robustness of simulated future forest dynamics. Our study highlights that comparing several alternative mortality formulations in DVMs provides valuable insights into the effects of process uncertainties on simulated future forest dynamics