Contrasting effects of environmental change factors on the radial growth of co-occurring European beech and fir trees across Europe

Under predicted climate change, silver fir (Abies alba) and European beech (Fagus sylvatica) are the most likely replacement species for the more heat- and drought-sensitive monocultures of Norway spruce (Picea abies) planted across large parts of continental Europe. Our current understanding of the climate-related adaptation potential of fir and beech mixtures is, however, limited. Here we compile and analyse 2855 tree-ring width (TRW) series from 17 mixed beech-fir forest sites in five European countries. Dendroecological techniques that combine various detrending methods with an application of documented environmental change trends reveal wide variation of radial growth between fir and beech across space and time. Coincidental with peak SO2 emissions, the growth of silver fir declined between 1950 and 1980 at most sites, whereas beech growth increased during this period. Correspondent to a significant warming trend from 1990–2010, average beech growth declined, but silver fir growth increased. Our observations of long-term growth trends support the replacement of spruce monocultures with multi-species mixtures that have demonstrated a higher tolerance of environmental changes

Influence of sampling and disturbance history on climatic sensitivity of temperature-limited conifers

The study was supported by the institutional project MSMT (CZ.02.1.01/0.0/0.0/16_019/0000803) and the Czech Ministry of Education (Project INTER-COST No. LCT17055).Accurately capturing medium- to low-frequency trends in tree-ring data is vital to assessing climatic response and developing robust reconstructions of past climate. Non-climatic disturbance can affect growth trends in tree-ring-width (RW) series and bias climate information obtained from such records. It is important to develop suitable strategies to ensure the development of chronologies that minimize these medium- to low-frequency biases. By performing high density sampling (760 trees) over a ~40-ha natural high-elevation Norway spruce (Picea abies) stand in the Romanian Carpathians, this study assessed the suitability of several sampling strategies for developing chronologies with an optimal climate signal for dendroclimatic purposes. There was a roughly equal probability for chronologies (40 samples each) to express a reasonable (r = 0.3?0.5) to non-existent climate signal. While showing a strong high-frequency response, older/larger trees expressed the weakest overall temperature signal. Although random sampling yielded the most consistent climate signal in all sub-chronologies, the outcome was still sub-optimal. Alternative strategies to optimize the climate signal, including very high replication and principal components analysis, were also unable to minimize this disturbance bias and produce chronologies adequately representing climatic trends, indicating that larger scale disturbances can produce synchronous pervasive disturbance trends that affect a large part of a sampled population. The Curve Intervention Detection (CID) method, used to identify and reduce the influence of disturbance trends in the RW chronologies, considerably improved climate signal representation (from r = 0.28 before correction to r = 0.41 after correction for the full 760 sample chronology over 1909?2009) and represents a potentially important new approach for assessing disturbance impacts on RW chronologies. Blue intensity (BI) also shows promise as a climatically more sensitive variable which, unlike RW, does not appear significantly affected by disturbance. We recommend that studies utilizing RW chronologies to investigate medium- to long-term climatic trends also assess disturbance impact on those series.PostprintPeer reviewe

When a tree dies in the forest : scaling climate-driven tree mortality to ecosystem water and carbon fluxes

Altres ajuts: COST FP1106 network STReESS.Drought- and heat-driven tree mortality, along with associated insect outbreaks, have been observed globally in recent decades and are expected to increase in future climates. Despite its potential to profoundly alter ecosystem carbon and water cycles, how tree mortality scales up to ecosystem functions and fluxes is uncertain. We describe a framework for this scaling where the effects of mortality are a function of the mortality attributes, such as spatial clustering and functional role of the trees killed, and ecosystem properties, such as productivity and diversity. We draw upon remote-sensing data and ecosystem flux data to illustrate this framework and place climate-driven tree mortality in the context of other major disturbances. We find that emerging evidence suggests that climate-driven tree mortality impacts may be relatively small and recovery times are remarkably fast (~4 years for net ecosystem production). We review the key processes in ecosystem models necessary to simulate the effects of mortality on ecosystem fluxes and highlight key research gaps in modeling. Overall, our results highlight the key axes of variation needed for better monitoring and modeling of the impacts of tree mortality and provide a foundation for including climate-driven tree mortality in a disturbance framework

Assessing the response of forest productivity to climate extremes in Switzerland using model-data fusion

The response of forest productivity to climate extremes strongly depends on ambient environmental and site conditions. To better understand these relationships at a regional scale, we used nearly 800 observation years from 271 permanent long-term forest monitoring plots across Switzerland, obtained between 1980 and 2017. We assimilated these data into the 3-PG forest ecosystem model using Bayesian inference, reducing the bias of model predictions from 14% to 5% for forest stem carbon stocks and from 45% to 9% for stem carbon stock changes. We then estimated the productivity of forests dominated by Picea abies and Fagus sylvatica for the period of 1960-2018, and tested for productivity shifts in response to climate along elevational gradient and in extreme years. Simulated net primary productivity (NPP) decreased with elevation (2.86 +/- 0.006 Mg C ha(-1) year(-1) km(-1) for P. abies and 0.93 +/- 0.010 Mg C ha(-1) year(-1) km(-1) for F. sylvatica). During warm-dry extremes, simulated NPP for both species increased at higher and decreased at lower elevations, with reductions in NPP of more than 25% for up to 21% of the potential species distribution range in Switzerland. Reduced plant water availability had a stronger effect on NPP than temperature during warm-dry extremes. Importantly, cold-dry extremes had negative impacts on regional forest NPP comparable to warm-dry extremes. Overall, our calibrated model suggests that the response of forest productivity to climate extremes is more complex than simple shift toward higher elevation. Such robust estimates of NPP are key for increasing our understanding of forests ecosystems carbon dynamics under climate extremes.Peer reviewe

Early-Warning Signals of Individual Tree Mortality Based on Annual Radial Growth

Tree mortality is a key driver of forest dynamics and its occurrence is projected to increase in the future due to climate change. Despite recent advances in our understanding of the physiological mechanisms leading to death, we still lack robust indicators of mortality risk that could be applied at the individual tree scale. Here, we build on a previous contribution exploring the differences in growth level between trees that died and survived a given mortality event to assess whether changes in temporal autocorrelation, variance, and synchrony in time-series of annual radial growth data can be used as early warning signals of mortality risk. Taking advantage of a unique global ring-width database of 3065 dead trees and 4389 living trees growing together at 198 sites (belonging to 36 gymnosperm and angiosperm species), we analyzed temporal changes in autocorrelation, variance, and synchrony before tree death (diachronic analysis), and also compared these metrics between trees that died and trees that survived a given mortality event (synchronic analysis). Changes in autocorrelation were a poor indicator of mortality risk. However, we found a gradual increase in inter- annual growth variability and a decrease in growth synchrony in the last similar to 20 years before mortality of gymnosperms, irrespective of the cause of mortality. These changes could be associated with drought-induced alterations in carbon economy and allocation patterns. In angiosperms, we did not find any consistent changes in any metric. Such lack of any signal might be explained by the relatively high capacity of angiosperms to recover after a stress-induced growth decline. Our analysis provides a robust method for estimating early-warning signals of tree mortality based on annual growth data. In addition to the frequently reported decrease in growth rates, an increase in inter-annual growth variability and a decrease in growth synchrony may be powerful predictors of gymnosperm mortality risk, but not necessarily so for angiosperms.Peer reviewe

Old World megadroughts and pluvials during the Common Era

Climate model projections suggest widespread drying in the Mediterranean Basin and wetting in Fennoscandia in the coming decades largely as a consequence of greenhouse gas forcing of climate. To place these and other “Old World” climate projections into historical perspective based on more complete estimates of natural hydroclimatic variability, we have developed the “Old World Drought Atlas” (OWDA), a set of year-to-year maps of tree-ring reconstructed summer wetness and dryness over Europe and the Mediterranean Basin during the Common Era. The OWDA matches historical accounts of severe drought and wetness with a spatial completeness not previously available. In addition, megadroughts reconstructed over north-central Europe in the 11th and mid-15th centuries reinforce other evidence from North America and Asia that droughts were more severe, extensive, and prolonged over Northern Hemisphere land areas before the 20th century, with an inadequate understanding of their causes. The OWDA provides new data to determine the causes of Old World drought and wetness and attribute past climate variability to forced and/or internal variability

Accuracy, realism and general applicability of European forest models

Forest models are instrumental for understanding and projecting the impact of climate change on forests. A considerable number of forest models have been developed in the last decades. However, few systematic and comprehensive model comparisons have been performed in Europe that combine an evaluation of modelled carbon and water fluxes and forest structure. We evaluate 13 widely used, state-of-the-art, stand-scale forest models against field measurements of forest structure and eddy-covariance data of carbon and water fluxes over multiple decades across an environmental gradient at nine typical European forest stands. We test the models\u27 performance in three dimensions: accuracy of local predictions (agreement of modelled and observed annual data), realism of environmental responses (agreement of modelled and observed responses of daily gross primary productivity to temperature, radiation and vapour pressure deficit) and general applicability (proportion of European tree species covered). We find that multiple models are available that excel according to our three dimensions of model performance. For the accuracy of local predictions, variables related to forest structure have lower random and systematic errors than annual carbon and water flux variables. Moreover, the multi-model ensemble mean provided overall more realistic daily productivity responses to environmental drivers across all sites than any single individual model. The general applicability of the models is high, as almost all models are currently able to cover Europe\u27s common tree species. We show that forest models complement each other in their response to environmental drivers and that there are several cases in which individual models outperform the model ensemble. Our framework provides a first step to capturing essential differences between forest models that go beyond the most commonly used accuracy of predictions. Overall, this study provides a point of reference for future model work aimed at predicting climate impacts and supporting climate mitigation and adaptation measures in forests

Accuracy, realism and general applicability of European forest models

Forest models are instrumental for understanding and projecting the impact of climate change on forests. A considerable number of forest models have been developed in the last decades. However, few systematic and comprehensive model comparisons have been performed in Europe that combine an evaluation of modelled carbon and water fluxes and forest structure. We evaluate 13 widely used, state-of-the-art, stand-scale forest models against field measurements of forest structure and eddy-covariance data of carbon and water fluxes over multiple decades across an environmental gradient at nine typical European forest stands. We test the models' performance in three dimensions: accuracy of local predictions (agreement of modelled and observed annual data), realism of environmental responses (agreement of modelled and observed responses of daily gross primary productivity to temperature, radiation and vapour pressure deficit) and general applicability (proportion of European tree species covered). We find that multiple models are available that excel according to our three dimensions of model performance. For the accuracy of local predictions, variables related to forest structure have lower random and systematic errors than annual carbon and water flux variables. Moreover, the multi-model ensemble mean provided overall more realistic daily productivity responses to environmental drivers across all sites than any single individual model. The general applicability of the models is high, as almost all models are currently able to cover Europe's common tree species. We show that forest models complement each other in their response to environmental drivers and that there are several cases in which individual models outperform the model ensemble. Our framework provides a first step to capturing essential differences between forest models that go beyond the most commonly used accuracy of predictions. Overall, this study provides a point of reference for future model work aimed at predicting climate impacts and supporting climate mitigation and adaptation measures in forests.Peer reviewe

The 2018 European heatwave led to stem dehydration but not to consistent growth reductions in forests

Heatwaves exert disproportionately strong and sometimes irreversible impacts on forest ecosystems. These impacts remain poorly understood at the tree and species level and across large spatial scales. Here, we investigate the effects of the record-breaking 2018 European heatwave on tree growth and tree water status using a collection of high-temporal resolution dendrometer data from 21 species across 53 sites. Relative to the two preceding years, annual stem growth was not consistently reduced by the 2018 heatwave but stems experienced twice the temporary shrinkage due to depletion of water reserves. Conifer species were less capable of rehydrating overnight than broadleaves across gradients of soil and atmospheric drought, suggesting less resilience toward transient stress. In particular, Norway spruce and Scots pine experienced extensive stem dehydration. Our high-resolution dendrometer network was suitable to disentangle the effects of a severe heatwave on tree growth and desiccation at large-spatial scales in situ, and provided insights on which species may be more vulnerable to climate extremes