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Agricultural and Forest Meteorology
Elsevier
Agricultural and Forest Meteorology

Elsevier

0168-1923

Agricultural and Forest Meteorology/Journal Agricultural and Forest MeteorologySCIISTP
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    Causes for the increase of early-season freezing events under a warmer climate at alpine Treelines in southeast Tibet

    Shen W.Zhang L.Luo T.
    10页
    查看更多>>摘要：? 2022 Elsevier B.V.Few data have demonstrated why early-season freezing events may increase under a warmer climate at alpine treelines, which is critical to understand the key limiting factors determining treeline dynamics under future climate warming. Here we test the hypothesis that the increase of early-season freezing events under a warmer climate is mainly associated with advanced onset of growing season and enhanced radiative cooling effect in the pre-monsoon season. We conducted 11-year observations of microclimate factors across north-facing and south-facing treelines in the Sergyemla Mountains, southeast Tibet. We found that the frequency, intensity, and duration of early-season freezing events were generally higher under a warmer climate on the south-facing slope or in the warmer years within a slope, in which the frequency of early-season freezing events significantly increased with increasing annual mean air-temperature. During 2006–2016, the frequency, intensity and duration of early-season freezing events typically showed a negative correlation with the onset date of growing season, while their frequency was positively correlated with the early-season global radiation. In each of both slopes, global radiation was significantly higher and long-wave radiation balance was much more negative on days with daily minimum air-temperature (Tmin) < 0 °C than with Tmin > 0 °C, indicating the generality of radiative cooling effect on early-season freezing events at high elevations. Our data support the hypothesis, revealing physical mechanisms for the increase of early-season freezing events with climate warming. The physical mechanisms should provide a general explanation for the topography-dependent pattern of tree species distribution and alpine treeline stability under climate warming in high mountainous regions like the Himalayas.
      原文链接:
    • NSTL
    • Elsevier

    Multi-year trend and interannual variability in soil respiration measurements collected in an urban forest ecosystem in Beijing, China

    Hao S.Bourque C.P.-A.Yang R.Jiang Y....
    7页
    查看更多>>摘要：? 2022 Elsevier B.V.Understanding the long-term trend and interannual variability in soil respiration (Rs) and their controlling factors, is essential to the prediction of soil carbon (C) losses in response to climate change. Knowledge in this field, however, particularly in urban forests remains largely absent. In this study, we analyzed long-term trends in continuous soil CO2 efflux and site-specific climatic data collected in an urban forest plantation in Beijing, China, over a 9-year period (i.e., 2011–2019). Collectively, annual Rs displayed an increasing trend over the study period with a rate of change of 4.31% per year, being strongly affected by changes in soil temperature (Ts). Annual Rs ranged from 447.59 to 622.79 g C m?2 year?1, yielding a coefficient of variation of 11.26%. Interannual variability in detrended Rs was largely controlled by spring precipitation (PPT), which likely modified Rs by influencing the thawing cycle in soils. The role of soil water content (SWC) in affecting Rs was assessed to be less important. A two-factor linear model combining spring PPT and annual mean Ts performed reasonably well in explaining annual Rs, producing a R2 of 0.55. This study identified different controls for trend and variation in Rs and the findings have important implications in the process-based modeling of soil C emissions in the area.
      原文链接:
    • NSTL
    • Elsevier

    Severe drought can delay autumn senescence of silver birch in the current year but advance it in the next year

    Dox I.Decoster M.Gasco A.Campioli M....
    14页
    查看更多>>摘要：? 2022Historically, the autumn dynamics of deciduous forest trees have not been investigated in detail. However, autumn phenological events, like onset of loss of canopy greenness (OLCG), onset of foliar senescence (OFS) and cessation of wood growth (CWG), have an important impact on tree radial growth and the entire ecosystem's seasonal dynamics. Here, we monitored the leaf and wood phenological events of silver birch (Betula pendula) at four different sites in ?s, southeastern Norway: (a) a natural mature stand, (b) a plantation on former agricultural ground, (c) young natural trees, and (d) young trees in pots under different fertilization levels. The study took place over four consecutive years (from 2017 to 2020), with a particular focus on 2018, a year in which there was a severe summer drought, and the next year, 2019, which featured more normal conditions. First, we provided a description of birch phenology within its mid-north distributional. Second, we showed that drought advanced CWG by about 5 to 6 weeks and it delayed OLCG and OFS up to 30 days. Third, we observed an unexpected advance in OLCG in 2019 compared to 2018 (30 days) and 2020 (14 days). OFS presented similar dynamics as OLCG, whereas CWG was advanced only in 2018. These findings might indicate lag-effects of severe drought on the next year autumn leaf phenology but not on wood growth. On the other hand, the comparison between the natural stand and the plantation showed that, under drought conditions, wood growth is more sensitive to site fertility than autumn leaf phenology. In summary, our study elucidated the autumn dynamics of an important deciduous forest species in the northern temperate zone and showed unexpected impacts of a severely dry and warm summer on the current and next year leaf phenology.
      原文链接:
    • NSTL
    • Elsevier

    High spatial resolution modelling of net forest carbon fluxes based on ground and remote sensing data

    Chirici G.Giannetti F.Chiesi M.Fibbi L....
    11页
    查看更多>>摘要：? 2022This paper presents the application of a recently proposed modelling strategy to yield high spatial resolution estimates of net forest carbon fluxes in Tuscany (Central Italy). The simulation of forest net primary production (NPP) and net ecosystem production (NEP) is based on the combination of remotely sensed and ancillary data which describe the main characteristics of local environment and vegetation. Distinctively, the methodology is driven by a map of growing stock volume (GSV) having a pixel size of 23 × 23 m2 and can therefore yield correspondingly high spatial resolution estimates of forest NPP and NEP. An advancement of the original methodology is also proposed based on the availability of a recently produced soil organic carbon map of Tuscany informative about biomass decomposition (heterotrophic respiration). The modified modelling strategy is applied over the period 2001–2005 and the obtained estimates are assessed against: i) ground observations of GSV current annual increment (CAI) collected for over 600 plots during the last National Forest Inventory of Italy; ii) a high spatial resolution reference NEP map obtained for a Mediterranean pine forest (San Rossore) by the integration of eddy covariance flux data and local CAI observations. Considering the complexity of the simulated processes and of the examined environment, the estimation accuracy achieved is satisfactory for both NPP and NEP. This supports the possibility of applying the proposed modelling strategy to estimate net carbon fluxes at high spatial resolution in other forest environments.
      原文链接:
    • NSTL
    • Elsevier

    Estimation of the effects of aerosol optical properties on peatland production in Rzecin, Poland

    Harenda K.M.Poczta P.Chojnicki B.H.Markowicz K.M....
    12页
    查看更多>>摘要：? 2022 The AuthorsThe productivity response of a peatland ecosystem in Rzecin, Poland, was determined based on varying aerosols abundant in the atmosphere. The study was done with the use of a multifactorial model that combined atmospheric and ecosystem modules to describe plant photosynthetic ability from different perspectives. The Gross Ecosystem Production (GEP) was calculated for real conditions in the period from May through September 2018. This period was characterized by increased air temperatures (1.4 °C) and reduced precipitation (17%), when compared to the long-term averages (1981–2010) for the studied area. This also aligned with expected direction of climate change predictions. The multifactorial model was used to show that, depending on the aerosol situation, the peatland ecosystem may react with an average increase (8.2%) as well as a decrease (6%) of GEP during the growing season. The modification of atmospheric optical properties with a step-wise increase of aerosol optical depth (AOD) by 0.2 in relation to the observed value, resulted in the increase of diffuse index (DI) of circa 22%, the decrease of photosynthetic photon flux density (PPFD) of circa 5%, and the increase of GEP of circa 8% in each of analyzed months. The GEP reduction (6%) was caused by the absorbing aerosol presence characterized by low single scattering albedo (SSA) value. Consequently, the CO2 uptake process could not be maximized by the ecosystem due to reduced levels of available radiant energy. Conversely, the effect of non-absorbing aerosols presence on GEP was found negligible due to the continental clean aerosols prevailed in the air mass during the study period. Generally speaking, the estimation of the effects of aerosol optical properties on Rzecin peatland production shows that more absorbing aerosols occurrence cause GEP reduction while AOD rise results in GEP gain.
      原文链接:
    • NSTL
    • Elsevier

    Assessing nitrous oxide (N2O) isotopic analyzer performance for in-field use

    Francis Clar J.T.Anex R.P.
    12页
    查看更多>>摘要：? 2022 The Author(s)Analysis of N2O isotope ratios is a way to apportion N2O production in soils among source pathways and develop mitigation strategies. Measurement systems employing a field-deployable LAS instrument coupled with automatic and dynamic soil flux chambers, where the soil emitted gas continuously circulates between the analyzer and the chamber can provide direct in situ N2O flux and N2O isotope ratio measurements with high temporal resolution. Reliable use of these measurements, however, requires quantification of measurement accuracy at high analyzer sampling rates - 2 seconds. We evaluated the variability of the measurements of an LAS isotope N2O analyzer – the OA-ICOS (Isotopic N2O Analyzer model 914–0027, Los Gatos Research Inc, Los Gatos, CA), over N2O concentrations observed in field experiments. We calculated the uncertainty of isotope ratios estimated using the Keeling plot method for representative soil N2O fluxes and chamber closure times. The variability of OA-ICOS isotopic ratio measurements is inversely related to N2O concentration leading to high uncertainty in soil emitted N2O isotope ratios estimated using the Keeling plot method in which low concentration measurements have the largest influence. Instrument precision evaluated using reference gasses was propagated through Monte Carlo simulation to predict system performance under a range of conditions. Model predictions of in situ measurement accuracy were evaluated with soil flux simulations using soil emitted gasses. Isotope ratios derived using OA-ICOS measurements during soil flux simulations deviated markedly from IRMS measurements. System performance was limited by the concentration dependence of N2O isotope ratio measurements and the suspected presence of interferents in soil emitted gasses. These characteristics of the OA-ICOS isotopic analyzer make it poorly suited for in situ source partitioning of soil emitted N2O. Until we overcome these limitations in situ N2O isotopic ratio measurements by OA-ICOS and automatic flux chambers are best used qualitatively.
      原文链接:
    • NSTL
    • Elsevier

    Roughness sublayer over vegetation canopy: A wind tunnel study

    Mo Z.Liu C.-H.Chow H.-L.Lam M.-K....
    14页
    查看更多>>摘要：? 2022Atmospheric flows in the inertial sublayer (ISL) and the roughness sublayer (RSL) are complicated by vegetation canopies. They subsequently modify the exchange of momentum and tracer fluxes between the plants and the overlying atmospheric surface layer (ASL). In this study, the flows over idealized vegetation canopies are modeled by wind tunnel experiments. Using fast-response, constant-temperature (CT) hot-wire anemometry (HWA), mean winds and turbulence are measured to test the sensitivity of the dynamics to the configurations of tree models. The drag coefficient measured is in the range of 4.0 × 10-3 ≤ Cd ≤ 7.6 × 10?3. The dimensionless profiles of mean and fluctuating velocities agree well with previous results obtained by wind tunnel experiments and large-eddy simulation (LES) over various vegetation canopies. Incorporating a correction function, a new analytical solution to the mean-wind-speed profile, which is applicable to both RSL and ISL continuously, is developed that is verified favorably by the current wind tunnel data. One of the key parameters, the RSL constant, is found in the range of 2.1 ≤ μ ≤ 2.6 that is larger than its counterpart over urban canopies. Unlike ISL, the skewness and kurtosis of flows show that RSL momentum transport is mainly governed by rare, high-speed, downdrafts (u’ > 0 and w’ < 0; sweep Q4) and massive, low-speed, updrafts (u’ < 0 and w’ > 0; ejection Q2). This finding concurs the dominant events unveiled by quadrant-hole analysis. The results contrast the dissimilarity between ISL and RSL that improve our understandings of their dynamics over vegetation canopies.
      原文链接:
    • NSTL
    • Elsevier

    Adapting to climate change precisely through cultivars renewal for rice production across China: When, where, and what cultivars will be required?

    Zhang J.Cao J.Tao F.Zhang L....
    14页
    查看更多>>摘要：? 2022 Elsevier B.V.Climate change is projected to have an important impact on crop productivity at broad regions of the world. Crop breeders across the globe have continuously been working on development of crop cultivars to adapt to climate change, the detailed information is necessary on when and where the adaptability of current cultivars will be broken and what cultivar traits will be required. Here, we developed a novel hybrid crop modelling approach that coupled a process-based crop model with machine learning and systematically assessed the impacts of climate change on rice productivity for 36 representative cultivars in China. We identified when, where, and what cultivars would be required for rice production to adapt to climate change precisely across China. We showed substantial differences in climate change impacts amongst cultivars. Current cultivars replacement could only alleviate but not offset the potential yield loss due to climate change in the future. Without adaptations and CO2 effect, nearly 67% of single rice and 46% of double rice cultivation areas would require cultivar renewal before 2050. Only two decades of leading time remain in the mid-lower reaches of the Yangtze River. The cultivars with a medium growth cycle, long grain-filling period, high photosynthetic capacity, and less spikelets should be breeding targets to adapt to climate change, although the ideotypic traits could be different for a specific environment and rice type.
      原文链接:
    • NSTL
    • Elsevier

    Simulation of soil CO2 efflux under different hydrothermal conditions based on general regression neural network

    Zhang L.Yan W.Liu Y.Liang X....
    11页
    查看更多>>摘要：? 2022 Elsevier B.V.Soil respiration (Rs) is an important component of global carbon (C) cycle and represents the second largest C exchange between atmosphere and geosphere. Regression models have been widely applied to describe Rs process and its relations to environmental factors in terrestrial ecosystems. However, the development of these semi-empirical regression model needed a large number of observation data in order to chives a reliable result. The successful performance of the regression model was highly dependent on data quality. In this study, a general regression neural network (GRNN) model and six validated two-factor-semi-empirical regression models were compared to stimulate changes of Rs under the influence of soil temperature (Tsoil) and soil moisture (Wsoil) alone and combination in camphor forests in subtropical China. The results showed the GRNN model produced greater accuracy than the regression models in predicting Rs. The R2 ranged 0.773-0.809 for the six two-factor regression models, but 0.84 for the GRNN model, with calculated RMSE of 0.404-442 in the regression models compared to 0.20 in the GRNN model. The dataset expanded by GRNN model could better fit the semi-empirical model than the observation dataset, which indicated the GRNN model had satisfactory generalization properties. Additionally, the GRNN model revealed the non-linear relationship between Rs and Wsoil when Wsoil was not a limiting factor, while the regression models were hard to detect the internet linkage. Therefore, GRNN model can not only be considered as a method to provide more accurate predication of Rs in forest ecosystems, but also provide an optional scheme for studying Rs under extreme and long-term climate change.
      原文链接:
    • NSTL
    • Elsevier

    Recent trends in the agrometeorological climate variables over Scandinavia

    Devasthale A.Karlsson K.-G.Carlund T.
    11页
    查看更多>>摘要：? 2022 Swedish Meteorological and Hydrological InstituteThe impacts of global climate change in response to increasing greenhouse gasses are spatio-temporally heterogeneous and are observed in a number of essential climate variables (ECVs). Among the ECVs that are highly relevant for the agriculture and forestry applications are clouds, precipitation and the incoming surface solar radiation (SIS). The past trends in these three agrometeorological ECVs and, more importantly, the co-variability among them can impact future agriculture and forestry policies and practices, their resilience and conservation. Therefore, using 37-year long climate data records spanning from 1982 to 2018 from the satellite- and surface based observing systems, we investigate the co-variability of trends in cloudiness, precipitation and SIS over Scandinavia during the summer months (April through September). The results reveal a complex nature of such co-variability among the trends in these three climate variables over Scandinavia. We report that the total cloudiness has decreased over much of Scandinavia. The decrease is most pronounced and statistically significant over southern Scandinavia in April, over the western coast in July and over much of northern Scandinavia in August. These decreasing trends are mainly due to reductions in the low and middle level clouds. The trends in all-sky incoming surface radiation are opposite in nature and broadly follow the spatio-temporal patterns of the trends in total cloudiness. The precipitation trends are heterogeneous, both spatially and temporally. The analysis of co-variability of trends reveals three distinct area-regimes that are relevant for assessing the changes in the land use and land cover.
      原文链接:
    • NSTL
    • Elsevier