Messori, GabrieleVico, GiuliaGalfi, Vera MelindaWu, Minchao...
10页
查看更多>>摘要：Jet streams are a key component of the climate system, whose dynamics couple closely to regional climate variability. Yet, the link between jet stream variability and vegetation activity has received little attention. Here, we leverage our understanding of the mid-latitude jet stream dynamics over the Euro-Atlantic sector to probe climate-vegetation interactions across Europe. We link indices related to the meridional location of the jet and the large-scale zonal wind speed with remotely-sensed vegetation greenness anomalies during locally-defined growing seasons. Correlations between greenness anomalies and jet latitude anomalies point to a control of the jet stream's variability on vegetation activity over large parts of Europe. This potential control is mediated by the jet latitude anomalies' correlations with temperature, soil moisture and downward surface solar radiation. The sign and strength of these correlations depend on location and time of the year. Furthermore, jet stream variability modulates conditions at the onset and end of the growing season. The link between jet latitude anomalies and vegetation greenness is not only specific to the climate zone, but also to the landclass and subperiod within the growing season. It is thus important to use a locally-defined growing season for interpreting the atmospheric controls on regional vegetation phenology. Results consistent with the correlation analysis emerge when focussing on local high or low greenness months only or on zonal wind speed anomalies, confirming the relevance of jet variability for vegetation activity.
查看更多>>摘要：Variations in phenology are regarded as a dynamic bio-indicator of global climate change. Rising incomes and the shift toward a diverse diet have been increasing the cash crop demand. However, the response of cash crop phenology to climate change and adaptive management practice remains largely unknown. In this study, using phenology records from 1991 to 2010, we separate the effects of climatic factors and management on phenological changes in the cash crops of sorghum, peanut, and canola based on the statistical and machine learning models. Our results show: (1) The sowing, emergence, three-leaf, and milk ripening date of sorghum showed a significantly (p < 0.05) advanced trend. The sowing, emergence, and five-leaf for canola likewise exhibited a significantly advanced trend (0.55 to 0.91 days a-1). The phenophases of the peanut were generally delayed (0.12 to 0.86 days a-1). (2) For sorghum, canola, and peanut, there is a delayed effect of increasing sunshine hours on heading/anthesis dates. The sowing date for sorghum and peanut delayed with the increased temperature. The three-leaf and milk ripening date of sorghum were sensitive to the wind speed. (3) Sunshine hours contributed to the extension of the whole growth period for sorghum, peanut, and canola, by 68.1, 60.7, and 40.0 %, respectively. The wind speed and temperature had comparable contributions to the maturity date, the former even dominating the heading date of sorghum. (4) Adaptive management practice partially offsets the effect of climate change and supports the length of the whole growth period for sorghum and peanut. Climate change exerts a positive effect on the vegetative growth period for three crops. Our results identified the main climatic factors regulating cash crop phenology. Wind speed must be incorporated in the process-based model to better account for the phenological variations associated with climate change.
查看更多>>摘要：Urban heat islands (UHI) exacerbates the heat-related risk associated with global warming, increasing morbidity and mortality of urban residents. While the impacts of the spatial pattern of urban greenspace (UG) and its change on urban heat have been widely examined, there is less understanding of the aggregate effect of the change of UG-considering the loss and gain of UG simultaneously -on urban temperature. This study aims to fill this gap by using Beijing, China as a case study. Using a newly developed index -dynamic index of UG (UGDI) that simultaneously measures the loss and gain of UG in a certain unit of analysis, we investigated how changes in UG affect the daytime and nighttime land surface temperature (LST). We found: (1) A substantial proportion (49.90%) of grids with increased UG cover had increased LST during the daytime, with a magnitude ranging from 0.02 to 1.82 ?, indicating that the increase in UG does not always result in reduction of LST. (2) UGDI had a significantly positive correlation with LST change, suggesting that increase in UG does not necessarily result in decrease of LST, which can be affected by the degree of dynamics of UG. (3) The evapotranspiration (ET) rate of vegetation for lost greenspace was higher than that of new greenspace, indicating that adding the same amount of UG might not able to provide the same amount of cooling effects provided by lost ones. Results can enhance our understanding on how (landscape) process affects ecological effect. Future research and practical manage-ment strategies shall move beyond net increase of UG and focus more on its change process. This finding provides new evidence for explaining the effect of the change of UG on LST, and offers new insights for planning and managing urban natural resource to enhance resilience of cities to climate warming.
查看更多>>摘要：Modeling vegetation phenology is crucial to assessing how climate change impacts carbon cycles in terrestrial ecosystems. The process-based biogeochemical model Biome-BGCMuSo is widely used for simulating carbon and water storages and fluxes of grassland ecosystems. However, the lack of accurate phenological information, such as the start of the growing season (SOS), impedes better simulations of the biogeochemical processes in the Tibetan Plateau (TP). Here, based on the snow-free satellite-derived SOS and the end of the growing season (EOS) in the TP during 1982-2018, we calibrated and validated three phenological models for SOS (i.e., the Biome-BGC phenological (BBGC) model, the heatsum growing season index (HSGSI) model, and the alpine meadow prognostic phenological (AMPP) model) and five phenological models for EOS (i.e., BBGC, HSGSI, AMPP, the low temperature and photoperiod multiplicative model induced by photoperiod (TPMP) and temperature (TPMT)) using particle swarm optimization (PSO) algorithm. For SOS, all three phenological models with calibrated parameters performed similarly and all captured the change in SOS well along gradients of aridity. The performance of BBGC, HSGSI, and AMPP models were largely improved with the calibration. The AMPP model simulated SOS with the lowest estimation errors with the mean absolute error (MAE) of 18.67 days and the Kling Gupta efficiency (KGE) of 0.47 in validation. For EOS, the calibrated HSGSI and AMPP models, with mean MAEs of 9.85 and 9.29 days, respectively, captured the change in EOS well along the gradients of aridity and performed better than other models. The calibration significantly improved the simulation performance of all five models. Therefore, the phenological models can be calibrated and validated at a large scale with snow-free satellite derived phenological data. Our study recommends that calibration and validation for the phenological model play a vital role in accurately simulating SOS and EOS in the regional carbon cycle simulation.
查看更多>>摘要：Phenology models are crucial tools for assessing climate change impacts in forestry, ecology and agriculture. Such models are typically calibrated with observational or experimental data and validated with a set of inde-pendent observations. While there have been extensive discussions about validation approaches, systematic studies assessing the effects of the calibration data on the predictive performance of the fitted model are scarce. We evaluated the impact of marginal seasons in the calibration data set on the predictive power of an integrated modeling framework (PhenoFlex) that was recently proposed to predict spring phenology in temperate trees. We calibrated PhenoFlex with phenology records of apple trees from a multi-season experiment (59 experimental seasons) that included five unusually warm winter seasons. For comparison, we excluded these marginal seasons in a second version of the analysis. We fitted the 12 model parameters to data, assessed model performance using a common validation data set and evaluated the chill and heat responses during dormancy for both versions. Despite high overall accuracy, our results indicated a better model performance (Root Mean Square Errors of 2.3 versus 5.5 days) when excluding the marginal seasons. We observed a similar shape for the chill response curve across versions but a greater chill effectiveness when including the marginal seasons. Fitted parameters suggest a hard drop in heat efficiency beyond the optimum temperature when including the marginal seasons, probably highlighting the need for more moderate conditions during model calibration. Our results demonstrate a good performance of PhenoFlex when calibration and validation data were comparable, but they also indicate risks involved in using the framework to project phenology under conditions that differ strongly from those used for calibration. Further evaluation and validation under experimentally or naturally occurring warm conditions may improve our understanding of the response of temperate trees to mild winter conditions.
查看更多>>摘要：The leaf area index (LAI) is an important indicator reflecting the growth status of vegetation and is widely used in agriculture, ecology, climate change, and other fields. The shortcomings of the currently available methods for manually measuring LAI include labor-intensive, low sampling frequency, and asynchronous data collection. Focusing on these issues, a LAI sensor based on hemispherical photogrammetry and an automatic network observation system (LAI-NOS) for LAI were developed, which consists of four parts: LAI sensor, sensor node, sink node, and online data management system. The LAI sensor measures LAI values based on hemispherical photography. The sensor node is responsible for controlling the sensor and obtaining the data measured by the LAI sensor. The sink node is responsible for local networking and communication with the remote server. Data storage, data management, data display, and sampling frequency are managed by the online data management system. Comparative studies with LAI-2200C and satellite products were also conducted in this study. The comparative study with LAI-2200C showed that the LAI measurements of different vegetation types from both sources were highly significantly correlated whether based on Pearson regression or Passing & Bablok regression. A preliminary study comparing LAI-NOS measurements with Sentinel-2 inversion LAI and MODIS LAI products (MOD15A2H) showed (1) all LAI-NOS nodes measurements agreed very well with Sentinel-2 inversion LAI in the experimental period (average R-2=0.94, RMSE=0.41); (2) the possible overestimate of Sentinel-2 inversion LAI was found in the middle stage of wheat (jointing-anthesis); (3) MOD15A2H and LAI-NOS measurements showed similar crop growth trends in long-term observations.
Dias-Junior, Cleo Q.Acevedo, OtavioOliveira, Pablo E. S.Tsokankunku, Anywhere...
15页
查看更多>>摘要：Understanding the processes that govern the mixing and transport of scalars within and above the Amazon Forest is of great importance for many environmental applications. The impact of atmospheric stability on the roughness sublayer (RSL) as well as the influence on it by the processes in the overlying atmosphere are investigated using measurements collected at the Atmospheric Tall Tower Observatory. Five different stabilities are defined according to the turbulent fluxes' behaviour. Ejections dominate the transport in the RSL. In near neutral and unstable conditions coherent structures propagate up to 2-3 times the canopy height (h) and intermittently penetrate in the lowest part of the forest where sweeps drive the transport processes. In the unstable regime a weakening of the wind inflection at the canopy top and a transition to a convective regime above z = 2 h are observed. In stable conditions three regimes were defined characterised by a progressive lowering of the RSL and the weakening of the mixing-layer type coherent structures. In the "weakly stable' regime the intense momentum and scalar fluxes appear driven by the coherent structures being able to penetrate inside the canopy intermittently coupling the flow above and within the forest. The "very stable' regime is characterized by weak winds, a weakening of coherent structures and a decrease of the turbulent fluxes inhibited by buoyancy. The definition of a "super stable' regime allowed the identification of a peculiar condition characterized by low-wind and weak coherent structures confined close to the canopy top and producing negligible transport. Submeso motions dominate the flow dynamics in this regime both above and inside the RSL. Multiresolution analysis highlights the ability of submeso motions to propagate inside the canopy and to modulate the exchange, particularly of scalars, fully driving the large positive CO(2 )flux observed inside the forest in the super stable regime.
查看更多>>摘要：Leaf mass per area (LMA) is an important indicator of plant functioning and photosynthetic capacity and is critical for understanding plant physiology and ecosystem function. Despite detailed and continuous spectral information offered in hyperspectral reflectance, LMA remains a difficult leaf characteristic to be retrieved due to its complex constituents and overlapping absorptions with leaf water. Traditional derivative analysis is commonly used to extract the absorption band positions and to resolve overlapping spectral features, but most cases are only limited to an integral derivative that ignores the asymptotic information between spectral curves. Recent advances in fractional-order derivative (FOD) based analyses, however, have shown their advantages in eliminating background noise as well as in extracting effective information from spectral information. We have thus investigated the potentials of using the fractional derivative indices to retrieve LMA based on a composite dataset consisting of 842 leaf samples from various species. The results demonstrated that the 0.3-order FOD indices provided the highest accuracies to trace LMA and, meanwhile, had the least sensitivity to random noise. Among the ten different index types examined in this study, the SR(1320, 1715) calculated from the 0.3-order derivative spectra had the best performance with an R-2 of 0.79. Furthermore, the band around 1715 nm was confirmed to be the wavelength with the highest relative absorption of LMA, while the band around 1320 nm was the non-absorbing wavelength for LMA, which could be applied as a base to describe the effects of other leaf constituents. The results of this study revealed the potential of low-order FOD indices to capture LMA and we foresee their wide applications in the future.
查看更多>>摘要：Thermal ecology studies on the ecophysiological responses of organisms to temperature involve two paradigms: physiological rates are driven by body temperature and not directly by the environmental temperature, and they are largely influenced not only by its mean but also its variance. These paradigms together have been largely applied to macro invertebrates and vertebrates but rarely to microorganisms. According to these paradigms, foliar fungal pathogens are expected to respond directly to the fluctuations in leaf temperature, rather than in air temperature. We determined experimentally the impact of two patterns of leaf temperature variation of equal mean temperature, but differing in their daily amplitude, on the development of Zymoseptoria tritici, a fungus infecting wheat leaves. The highest daily thermal amplitude resulted in two detrimental effects for the pathogen fitness: an increase in the length of the latent period, i.e. the 'generation time' of the fungus when infecting its host plant, and a decrease in the density of fruiting bodies on the leaves. We discussed these empirical results, mainly the impact of both the daily thermal amplitude and the fluctuation frequency on the pathogen development in planta, in the light of the mathematical effect of the integration of non-linear functions. We concluded that it is necessary to take into account daily leaf temperature amplitudes to improve our understanding and prediction of the development of foliar fungal pathogens and other micro-organisms living in the phyllosphere in the climate change context.
NSTL
Elsevier