Agricultural and Forest Meteorology最新文献

Cold stress seriously affects rice yield in Northeast China and, as a result of climate change, there are new trends in the characterization of cold damage. Accurate simulation of water temperature in paddy fields and assessment of cold damage hazard can contribute to improving the accuracy of agrometeorological disaster risk assessment in the context of climate change. Hence, in this study, first, we simulated the water temperature of paddy fields based on the paddy field energy-balance model and evaluated the simulation results. Subsequently, a composite cooling-degree-day (CCDD) indicator for rice fields was constructed based on water and air temperatures to characterize cold stress and identify cold damage events. Finally, a cold damage hazard-assessment model was constructed for rice based on the frequency and intensity of cold damage to assess cold damage hazard in Northeast China from 1979 to 2018. The results showed that the root-mean-square error between simulated and observed water temperatures of the rice field energy-balance model was 0.45, which means that the model accurately simulated the water temperature of the rice field on a large spatial scale. In 2004, cold damage to late-maturity rice accounted for 30% of the total study area, which was one of the years with most severe cold damage in late-maturity rice-growing areas thus far in the 21st century. Water temperature affected 76.4% of the area in 2004, and was related to radiation and saturated vapor pressure. The low-hazard areas accounted for more than 20% in 2009–2018, and the high-hazard areas were still higher than 10%, indicating that the threat of cold damage in the northeastern region of China remained severe as the climate has become increasingly warm.

In semi-arid and arid regions, crops face elevated atmospheric demands and endure prolonged periods of moderate to severe water scarcity. In this context, this study investigated the effectiveness of the photochemical reflectance index (PRI) and a normalized surface temperature index (T_norm) for proxy detection of the water stress of winter wheat crops. Furthermore, the potential of PRI for characterizing water, atmospheric or photo-inhibition stress, and wheat transpiration was assessed over experimental drip-irrigated crop fields in the Haouz plain, central Morocco. In practice, PRI observations were compared to agro-environmental variables such as Leaf Area Index (LAI), Available Water Content (AWC) at a root zone depth, net Radiation (R_n), Vapor Pressure Deficit (VPD) and the wheat transpiration derived from sap flows, lysimeters and a crop water balance model. Due to the strong relationship between PRI and LAI (R² = 0.91), another index named PRI_j was derived to correct for this effect. The PRI_j was found to be independent of structural effects related to LAI and significantly correlated with AWC (R² = 0.85). Using the PRI_j index, we can reflect the level of water stress experienced by the wheat field throughout the experiment with an R² of 0.69 for a FAO-56 water stress coefficient (K_s) of less than 1. Under dry conditions, for an AWC below 30%, the correlation between AWC and T_norm gives an R² of 0.29. However, comparison of PRI_j with the T_norm index showed that PRI_j is an early water stress index and provides information on the state of the vegetation cover at all stages of wheat development. The study's findings can have a significant impact on the use of the PRI as a water stress indicator, helping in the optimal irrigation of crops.

Our understanding of water and carbon cycles and their coupling has advanced significantly over the last six decades. In this review, we will examine the progress made since the 1960s and explore how key developments in the studies of water and carbon cycles on land have influenced the way we model these two cycles from leaf to global scales. We will particularly focus on the Penman-Monteith equation for calculating evapotranspiration, the biochemical model of leaf photosynthesis, and the model of stomatal conductance.

These three models developed over three decades ago have been widely adopted in the studies of water and carbon cycle from leaf to global scales. The success of these models lie in their sound representation of the basic biophysical and biochemical processes with relative simplicity. Their wide adoption was also assisted by the rapid development of portable leaf gas exchange instruments and field deployment of eddy covariance techniques, which provide the data for estimating the key model parameters and for model evaluation and improvement.

Over the last two decades, rapid advances in remote sensing, global eddy flux networks, and computation have led to a rapid growth of different approaches for estimating water and carbon fluxes. This review compares the simulated global gross primary production, evapotranspiration and ecosystem water use efficiency and their trends using these different approaches, and finds that significant progress has been made in understanding their spatial patterns, interannual variations and trends. However, significant divergences remain among them.

Looking ahead, we identify several key areas where significant progress is likely, particularly through the applications of machine learning and ecological forecasting. We also anticipate the development of new theories by integrating theoretical understanding with increasing observations from ground and space.

Given the prevailing uncertainties surrounding regional climate variability in southeastern Brazil, it is necessary to explore proxy records. The present dendrochronological study investigates the climate variations in the Neotropical estuarine system of the Rio Doce basin based on tree-rings records of 40 trees of Terminalia catappa Linn. The study demonstrates that annual growth rings of the species record the variations in regional precipitation, streamflow of the Rio Doce basin and surface temperature of the south Atlantic ocean. The variation in the South Atlantic Ocean Dipole Index (SAODI) directly affects precipitation and indirectly influences growth ring increment. The strong synchrony among the trees highlights the marked effect of precipitation seasonality regulated by SAODI. The trees exhibit robust growth during the dry period when Rio Doce's rains and streamflow decrease, emphasizing the potential of this chronology for climate and hydrological monitoring. The chronology of T. catappa, despite being short, is the first to provide information on the climate variability of a South America estuary ecosystem. Future studies should verify the influences of precipitation and SAODI on the growth of long-lived species aiming climate reconstructions in the region.

Mechanistic modelling is gradually replacing empiricism in crop models, focusing on leaf-level physiological processes. This shift necessitates simulating crop surface temperature at infra-canopy sub-daily scales but many crop models still rely on empirical formulations for canopy temperature estimation, typically on a daily basis. We developed MONTPEL, a multi-component Penman-Monteith model that allows simulating the crop energy balance with flexible canopy representations (“BigLeaf” vs. “Layered”, “Lumped” vs. “Sunlit-Shaded”) and accounts for atmospheric stability conditions. We analyzed the model behavior, sensitivity and accuracy, using measurements from four wheat (Triticum aestivum L.) experiments conducted under varying pedoclimatic and water stress conditions. Measurements included hourly energy balance terms (total net radiation, soil heat flux, sensible and latent energy fluxes), hourly temperature of the canopy surface or of leaves at different depths inside the canopy, and sunlit and shaded leaf temperatures around solar noon at different dates. MONTPEL reproduced the measured energy balance terms with a root mean square error (RMSE) between 21 and 87 Wm^-2 and a coefficient of determination (R²) exceeding 0.65. The model's accuracy in simulating canopy temperature, with RMSE ≤ 2.2 °C and R² ≥ 0.92, remained consistent regardless of measurement scale. Adjusting the aerodynamic resistance for atmospheric stability minimized simulated canopy temperature errors, notably in semi-arid conditions. Crop latent energy flux and temperature were most sensitive to the maximal stomatal conductance ($g_{s,\text{max}}$) parameter. However, using a single $g_{s,\text{max}}$ value across the simulated experiments yielded satisfactory results, suggesting a weak sensitivity to the temporal and site-to-site variability of $g_{s,\text{max}}$. Distinguishing sunlit from shaded canopy fractions systematically resulted in lower latent energy fluxes compared to “Lumped” canopy representation results. Analysis identified limitations in the multi-component approach, particularly an unrealistic uniform temperature shift across leaf layers when soil surface temperature changes.

Plant area density measurements provide spatially explicit information about the density and distribution of canopy elements. This information is needed for modeling of the forest radiation regime, climate and for other ecological applications. Terrestrial laser scanning (TLS) provides detailed information about canopy structure, but it cannot be used for monitoring large areas. Airborne laser scanning (ALS) uses similar methods to measure plant area density, but due to the larger beam footprints, the scale at which this information can be obtained is coarser than with TLS. The volumetric nature of the ALS measurement poses unique geometric challenges to plant area measurement methods, as assuming an infinitesimal beam size may lead to large errors. Further, the use of voxel grids with ALS measurements may increase errors in plant area measurements, as these grids require discrete spatial allocation of information.

In this study, we apply a spatial weighting technique to ray-traced measurements of plant area from ALS data. This spatial weighting scheme allows continuous allocation of trajectory information of ALS pulses, avoiding discontinuity introduced by voxel grids.

Our data consisted of high density ALS waveform data (over 40 points/m${}^2$) in 33 plots across two study sites in Finland and Estonia. We compared the plant area index (PAI) obtained through this new measurement method to PAI measurements from hemispheric photography (HP) and TLS, and to ALS with a voxel grid. We found PAI, measured at agrid spacing of 0.6 m, correspond best to HP and TLS measurements. Occlusion severely biased PAI at 0.2 m spacing. With increasing grid spacing, PAI estimates become increasingly biased because of clumping effects at small scales. Continuously sampled PAI measurements corresponded closer to reference values than voxel-based PAIs, indicating that a spatially weighted approach avoids bias from partitioning the volumetric ALS beams into voxels.

Fire frequency in boreal forests has increased via longer burning seasons, drier conditions, and higher temperatures. However, fires have historically self-regulated via fuel limitations, mediating the effects of changes in climate and fire weather. Early post-fire boreal forests (10–15 years postfire) are often dominated by mixed conifer-broadleaf or broadleaf regeneration, considered less flammable due to the higher foliar moisture of broadleaf trees and shrubs compared to their more intact conifer counterparts. However, the strength of self-regulation in the context of changing fire weather and climate combined with the emergence of novel broadleaf forest communities and structures remains unclear. We quantified fuel composition, abundance, and structure in burned and reburned forests in Interior Alaska and used a physics-based fire behavior model (the Wildland-Urban Interface Fire Dynamics Simulator) to simulate how these unique patterns of fuel influence potential rates and sustainability of fire spread. In once-burned forests dominated by mixed conifer-broadleaf regeneration, extreme fire weather conditions allowed for sustained fire spread, suggesting that intense fire conditions can enable reburning, even 10 to 15 years following a previous high-severity fire. However, fire spread was not sustained in thrice-burned regenerating broadleaf forests, where regeneration was often dense but more clumped, and thus less connected, separated by patches of bare soil. Crown fire traveled an average of 50 meters into thrice-burned forests before dying out, even under extreme fire weather conditions. This work suggests that fire spread may be possible in once-burned regenerating forests under extreme fire weather conditions but may be more limited in less connected and less fuel abundant thrice-burned regenerating forests, at least within the 10–15-year window post-fire.

Large-scale modes of climate variability influence forest fire activity and may modulate the future patterns of natural disturbances. We studied the effects of long-term changes in climate upon the fire regime in the red pine forests of eastern North America using (a) a network of sites with dendrochronological reconstructions of fire histories over 1700–1900 A.D., (b) reconstructed chronologies of climate indices (1700–1900), and (c) 20th century observational records of climate indices, local surface climate and fire (1950s-2021). We hypothesized that (H1) there are states of atmospheric circulation that are consistently associated with increased fire activity, (H2) these states mark periods of increased climatological fire hazard, and (H3) the observed decline in fire activity in the 20th century is associated with a long-term decline in the frequency of fire-prone states.

At the annual scale, years with significantly higher fire activity in the reconstructed and modern fire records were consistently associated with the positive phases of the Pacific North American pattern (PNA), either independently or in combination with the positive phase of the El Niño-Southern Oscillation index (ENSO). During years with both ENSO and PNA in their positive state, the region experienced positive mid-tropospheric heights and temperature anomalies resulting in drought conditions. The fire-prone climate states identified in the reconstructed records became less frequent in 1850 but re-emerged in the 20th century. While our study did not demonstrate a direct influence of climate on the observed decrease in fire activity in the 20th century, it does reveal a clear climate signal embedded within the fire history reconstruction of the region over the past centuries. This study underscores the importance of considering large-scale climatic patterns in understanding historical fire regimes and highlights their role for future fire dynamics in the region and shaping ecological effects of future fires.

Both plant litter and roots are major sources of soil carbon (C) pools, however, the relative contributions of these two C input pathways to soil respiration, especially in different forest types, are largely unexplored, leading to a great uncertainty in estimating soil C sinks. As part of a field experiment with five-year (2016–2020) C input manipulations in three forests all between the subtropical and warm temperate region, this study was conducted to explore the responses of soil respiration to litter addition, litter removal, and root exclusion in a coniferous forest, a broadleaved forest, and a mixed broadleaf-conifer forest. Our results showed that litter addition enhanced soil respiration by 9.57 %, 15.5 %, and 24.5 % in the coniferous, broadleaved, and mixed forests, whereas litter removal decreased it by 4.06 % and 8.30 % in the coniferous and broadleaved forests across the five years due to the changes in soil microclimate and litter-derived C sources as well as a potential priming effect in the soil. Root exclusion reduced soil respiration in all the three forests, but its effect did not differ with that of litter removal, primarily attributing to the indistinctive deviation between these two C input pathways on soil microbial biomass. The influences of different C inputs on soil respiration varied with forest types, with interactions of root exclusion with litter manipulations occurring in the coniferous and broadleaved forests but additive effects of those in the mixed broadleaf-conifer forest. Our findings indicate different responses of soil respiration to plant litter and root manipulations in diverse forests, and imply that rational regulating of plant-derived C inputs can help to reduce soil C loss under climate change scenarios.

The non-closure of surface energy balance, often encountered in eddy covariance (EC) measurements, raises a critical query: does this non-closure lead to underestimated scalar fluxes, particularly CO₂ flux (Fc), when using the same theoretical framework in EC? To address this question, we utilize high-resolution large-eddy simulations (LESs) to explore correlations between energy flux imbalances and Fc imbalances in convective boundary layers, considering both homogeneous and idealized heterogeneous surfaces. Our findings reveal that the unsteady CO₂ or storage represents a leading factor influencing Fc imbalance, especially notable when the entrainment ratio for Fc is large. Even in scenarios with uniform surface Fcs, heterogeneous thermally-generated turbulence resulting from variable surface sensible heat flux (H) can induce substantial horizontal flux divergence, magnifying Fc imbalance. While a linear correlation between the energy flux imbalance and Fc imbalance arises under shared causative mechanisms (e.g., storage), complex correlations emerge if their influencing factors differ, contingent upon surface heterogeneity and site location. This complexity underscores the limitations in applying the closing methods for energy flux imbalance to the Fc imbalance.