Information on the onset of leaf senescence in temperate deciduous trees and comparisons on its assessment methods are limited, hampering our understanding of autumn dynamics.
We compare five field ...proxies, five remote sensing proxies and two data analysis approaches to assess leaf senescence onset at one main beech stand, two stands of oak and birch, and three ancillary stands of the same species in Belgium during 2017 and 2018.
Across species and sites, onset of leaf senescence was not significantly different for the field proxies based on Chl leaf content and canopy coloration, except for an advanced canopy coloration during the extremely dry and warm 2018. Two remote sensing indices provided results fully consistent with the field data. A significant lag emerged between leaf senescence onset and leaf fall, and when a threshold of 50% change in the seasonal variable under study (e.g. Chl content) was used to derive the leaf senescence onset.
Our results provide unprecedented information on the quality and applicability of different proxies to assess leaf senescence onset in temperate deciduous trees. In addition, a sound base is offered to select the most suited methods for the different disciplines that need this type of data.
Recent temperature increases have elicited strong phenological shifts in temperate tree species, with subsequent effects on photosynthesis. Here, we assess the impact of advanced leaf flushing in a ...winter warming experiment on the current year’s senescence and next year’s leaf flushing dates in two common tree species: Quercus robur L. and Fagus sylvatica L. Results suggest that earlier leaf flushing translated into earlier senescence, thereby partially offsetting the lengthening of the growing season. Moreover, saplings that were warmed in winter–spring 2009–2010 still exhibited earlier leaf flushing in 2011, even though the saplings had been exposed to similar ambient conditions for almost 1 y. Interestingly, for both species similar trends were found in mature trees using a long-term series of phenological records gathered from various locations in Europe. We hypothesize that this long-term legacy effect is related to an advancement of the endormancy phase (chilling phase) in response to the earlier autumnal senescence. Given the importance of phenology in plant and ecosystem functioning, and the prediction of more frequent extremely warm winters, our observations and postulated underlying mechanisms should be tested in other species.
•A two-year warming experiment was conducted using saplings of three deciduous tree species (oak, beech and birch).•The temperature sensitivity of leaf unfolding to six different warming levels was ...quantified.•Different warming levels elicited different levels of advancement in leaf unfolding.•A significant sigmoid correlation between chilling and forcing was found.•Warming did not result in further advancement of leaf unfolding in oak and beech, when it exceeded a threshold of +4°C.
Phenological events are sensitive to climate change, and a clear advancement of spring leaf phenology has been well documented. However, the observed phenological trends cannot be directly used to forecast future changes because the underlying mechanisms are still unclear. We conducted a two-year experimental warming experiment using one-meter-high saplings of birch (Betula pendula L.), oak (Quercus robur L.) and beech (Fagus sylvatica L.). The main objective of this study was to quantify the temperature sensitivity of leaf unfolding to six different warming levels. The results suggested that leaf unfolding dates were significantly advanced with warming for all species in both experimental years. However, different warming treatments elicited different leaf unfolding responses. At low and moderate warming (<+4°C), the sensitivity of leaf unfolding to temperature (changes in days per °C) increased with warming in all three studied species. For birch, the temperature sensitivity continued to increase with additional warming. For oak and beech, in contrast, the temperature sensitivity dramatically decreased when warming exceeded +4°C. Our findings confirm that continued and intense warming may not result in further advances of leaf unfolding in the late successional species oak and beech, if the warming exceeds a certain threshold leading to insufficient chilling temperatures for dormancy release.
Both increasing and decreasing 20th century growth trends have been reported in forests throughout Europe, but only for few species and areas suitable modelling techniques have been used to ...distinguish individual tree growth (operating on a local scale) from growth change due to exogenous factors (operating on a broad geographical scale). This study relates for the first time observed growth changes, in terms of basal area increment (BAI) of dominant trees of pedunculate oak, common beech and Scots pine, in north-west European temperate lowland forests (Flanders) to climate, atmospheric CO
2
and tropospheric O
3
concentrations, N deposition, site quality and forest structure for more than a century (the period 1901–2008), applying mixed models. Growth change during the 20th century is observed for oak (increasing growth) and beech (increasing growth until the 1960s, growth decline afterwards), but not for pine. It was possible to relate growth change of oak and beech to climate time series and N deposition trends. Adding time series for CO
2
and O
3
concentration did not significantly improve model results. For oak and beech a switch from positive to negative growth response with increasing nitrogen deposition throughout time is observed. Growth increase for oak is mainly determined by the interaction between growing season temperature and soil water recharge. It is reasonable to assume that the observed growth trend for oak will continue for as long as early season water availability is not compromised. The decreasing trend in summer relative air humidity observed since the 1960s in the study area can be a main cause of recent beech BAI decrease. A further growth decline of beech can be expected, independent of site quality.
Plants use only a fraction of their photosynthetically derived carbon for biomass production (BP). The biomass production efficiency (BPE), defined as the ratio of BP to photosynthesis, and its ...variation across and within vegetation types is poorly understood, which hinders our capacity to accurately estimate carbon turnover times and carbon sinks. Here, we present a new global estimation of BPE obtained by combining field measurements from 113 sites with 14 carbon cycle models. Our best estimate of global BPE is 0.41 ± 0.05, excluding cropland. The largest BPE is found in boreal forests (0.48 ± 0.06) and the lowest in tropical forests (0.40 ± 0.04). Carbon cycle models overestimate BPE, although models with carbon–nitrogen interactions tend to be more realistic. Using observation‐based estimates of global photosynthesis, we quantify the global BP of non‐cropland ecosystems of 41 ± 6 Pg C/year. This flux is less than net primary production as it does not contain carbon allocated to symbionts, used for exudates or volatile carbon compound emissions to the atmosphere. Our study reveals a positive bias of 24 ± 11% in the model‐estimated BP (10 of 14 models). When correcting models for this bias while leaving modeled carbon turnover times unchanged, we found that the global ecosystem carbon storage change during the last century is decreased by 67% (or 58 Pg C).
We quantify the global value of biomass production efficiency (BPE) by a number of field measurements with the results of terrestrial carbon cycle models, via an emergent‐constraint approach. We found that carbon cycle models overestimate global BPE, and therefore overestimate global biomass production, although models with carbon–nitrogen interactions show less model–data mismatch. Correcting models for this bias while leaving modeled carbon turnover times unchanged, the global ecosystem carbon storage change during the last century is decreased by 67% (or 58 Pg C/year).
Budburst phenology is a key driver of ecosystem structure and functioning, and it is sensitive to global change. Both cold winter temperatures (chilling) and spring warming (forcing) are important ...for budburst. Future climate warming is expected to have a contrasting effect on chilling and forcing, and subsequently to have a non-linear effect on budburst timing. To clarify the different effects of warming during chilling and forcing phases of budburst phenology in deciduous trees, (i) we conducted a temperature manipulation experiment, with separate winter and spring warming treatments on well irrigated and fertilized saplings of beech, birch and oak, and (ii) we analyzed the observations with five temperature-based budburst models (Thermal Time model, Parallel model, Sequential model, Alternating model, and Unified model). The results show that both winter warming and spring warming significantly advanced budburst date, with the combination of winter plus spring warming accelerating budburst most. As expected, all three species were more sensitive to spring warming than to winter warming. Although the different chilling requirement, the warming sensitivity was not significantly different among the studied species. Model evaluation showed that both one- and two- phase models (without and with chilling, respectively) are able to accurately predict budburst. For beech, the Sequential model reproduced budburst dates best. For oak and birch, both Sequential model and the Thermal Time model yielded good fit with the data but the latter was slightly better in case of high parameter uncertainty. However, for late-flushing species, the Sequential model is likely be the most appropriate to predict budburst data in a future warmer climate.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Most manipulation experiments simulating global change in tundra were short-term or did not measure plant growth directly. Here, we assessed the growth of three shrubs (Cassiope tetragona, Empetrum ...hermaphroditum and Betula nana) at a subarctic heath in Abisko (Northern Sweden) after 22 years of warming (passive greenhouses), fertilisation (nutrients addition) and shading (hessian fabric), and compare this to observations from the first decade of treatment. We assessed the growth rate of current-year leaves and apical stem (primary growth) and cambial growth (secondary growth), and integrated growth rates with morphological measurements and species coverage. Primary- and total growth of Cassiope and Empetrum were unaffected by manipulations, whereas growth was substantially reduced under fertilisation and shading (but not warming) for Betula. Overall, shrub height and length tended to increase under fertilisation and warming, whereas branching increased mostly in shaded Cassiope. Morphological changes were coupled to increased secondary growth under fertilisation. The species coverage showed a remarkable increase in graminoids in fertilised plots. Shrub response to fertilisation was positive in the short-term but changed over time, likely because of an increased competition with graminoids. More erected postures and large, canopies (requiring enhanced secondary growth for stem reinforcement) likely compensated for the increased light competition in Empetrum and Cassiope but did not avoid growth reduction in the shade intolerant Betula. The impact of warming and shading on shrub growth was more conservative. The lack of growth enhancement under warming suggests the absence of long-term acclimation for processes limiting biomass production. The lack of negative effects of shading on Cassiope was linked to morphological changes increasing the photosynthetic surface. Overall, tundra shrubs showed developmental plasticity over the longer term. However, such plasticity was associated clearly with growth rate trends only in fertilised plots.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Understanding tree growth and carbon sequestration are of crucial interest to forecast the feedback of forests to climate change. To have a global understanding of the wood formation, it is necessary ...to develop new methodologies for xylogenesis measurements, valid across diverse wood structures and applicable to both angiosperms and gymnosperms. In this study, the authors present a new workflow to study xylogenesis using high-resolution X-ray computed tomography (HRXCT), which is generic and offers high potential for automatization. The HXRCT-based approach was benchmarked with the current classical approach (microtomy) on three tree species with contrasted wood anatomy (
Pinus nigra, Fagus sylvatica
, and
Quercus robur
). HRXCT proved to estimate the relevant xylogenesis parameters (timing, duration, and growth rates) across species with high accuracy. HRXCT showed to be an efficient avenue to investigate tree xylogenesis for a wide range of wood anatomies, structures, and species. HRXCT also showed its potential to provide quantification of intra-annual dynamics of biomass production through high-resolution 3D mapping of wood biomass within the forming growth ring.
► Six budburst models were tested on four tree species using Bayesian model comparison. ► Across species, one-phase models (considering only warming) performed best. ► Among the two-phase models ...(with chilling phase), the Sequential model performed best. ► Complete chilling at all sites caused lower likelihood of two-phase models. ► In warmer regions or future climate, two-phase models may still perform better.
Phenology models are tools to analyze changes in the timing and duration of the growing season. During the past three decades different budburst models have been developed, but, so far, no consensus model has been found to accurately predict budburst date across different tree species. The aim of this study was to estimate the performance of six different temperature-driven models of leaf budburst (thermal time, thermal period fixed, sequential, parallel, alternating, unified) for four temperate tree species in Belgium (birch, chestnut, oak, beech). The models were parameterized using a Bayesian approach. The performance of these models was compared using Bayesian model comparison (BMC) and root mean square error (RMSE).
Model comparison showed that the two models that do not include a calculation of chilling requirement were the best for the studied four tree species. The Sequential model (SM) was the third most plausible model for predicting budburst, having a higher probability to be correct than the other two-phase models combining a chilling phase with a forcing phase. This suggested that in our budburst observation dataset, the chilling requirement was probably always fulfilled, making the date of budburst controlled by forcing temperature. We cannot rule out that in warmer regions or future warmer conditions, chilling may become insufficient and a sequential pattern of chilling and forcing may become most appropriate to simulate budburst date. Parameter analysis showed that the last month prior to budburst had the greatest impact on determining the date of bud opening in the case of birch and chestnut, whereas the last 3 months were the main determinants for oak and beech, the two later flushing species. Validation showed that the models that fitted the parameterization data well had much poorer performance when tested with independent data. This indicates that other factors (e.g. photoperiod) might affect the budburst process and/or model parameterization (determining the sensitivity of budburst to temperature) substantially change between different localities.
About 25% of European livestock intake is based on permanent and sown grasslands. To fulfill rising demand for animal products, an intensification of livestock production may lead to an increased ...consumption of crop and compound feeds. In order to preserve an economically and environmentally sustainable agriculture, a more forage based livestock alimentation may be an advantage. However, besides management, grassland productivity is highly vulnerable to climate (i.e., temperature, precipitation, CO2 concentration), and spatial information about European grassland productivity in response to climate change is scarce. The process-based vegetation model ORCHIDEE-GM, containing an explicit representation of grassland management (i.e., herbage mowing and grazing), is used here to estimate changes in potential productivity and potential grass-fed ruminant livestock density across European grasslands over the period 1961-2010. Here "potential grass-fed ruminant livestock density" denotes the maximum density of livestock that can be supported by grassland productivity in each 25 km × 25 km grid cell. In reality, livestock density could be higher than potential (e.g., if additional feed is supplied to animals) or lower (e.g., in response to economic factors, pedo-climatic and biotic conditions ignored by the model, or policy decisions that can for instance reduce livestock numbers). When compared to agricultural statistics (Eurostat and FAOstat), ORCHIDEE-GM gave a good reproduction of the regional gradients of annual grassland productivity and ruminant livestock density. The model however tends to systematically overestimate the absolute values of productivity in most regions, suggesting that most grid cells remain below their potential grassland productivity due to possible nutrient and biotic limitations on plant growth. When ORCHIDEE-GM was run for the period 1961-2010 with variable climate and rising CO2, an increase of potential annual production (over 3%) per decade was found: 97% of this increase was attributed to the rise in CO2, -3% to climate trends and 15% to trends in nitrogen fertilization and deposition. When compared with statistical data, ORCHIDEE-GM captures well the observed phase of climate-driven interannual variability in grassland production well, whereas the magnitude of the interannual variability in modeled productivity is larger than the statistical data. Regional grass-fed livestock numbers can be reproduced by ORCHIDEE-GM based on its simple assumptions and parameterization about productivity being the only limiting factor to define the sustainable number of animals per unit area. Causes for regional model-data misfits are discussed, including uncertainties in farming practices (e.g., nitrogen fertilizer application, and mowing and grazing intensity) and in ruminant diet composition, as well as uncertainties in the statistical data and in model parameter values.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
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