Larger diurnal temperature range undermined later autumn leaf senescence with warming in Europe

Aim

Climate change regulates autumn leaf senescence date (LSD), exhibiting a strong phenological control of plant carbon uptake. Unlike the delaying effect of daily mean temperature (T_mean) on LSD, the impact of warming asymmetry in daytime and nighttime, as evidenced by variations of the diurnal temperature range (DTR), remains elusive. The objectives of this study were to investigate physiological and ecological impacts of DTR on LSD using long-term in situ observations and to predict the future trends of LSD under warming.

Location

Europe.

Time period

1950–2015.

Major taxa studied

Plant phenology.

Methods

We used partial correlation analysis, multiple linear regression and ridge regression to explore the impacts of DTR on LSD. To quantify the importance of potential drivers of LSD, we trained random forest models and applied the SHapley Additive exPlanations method to isolate the marginal contributions of each predictor on LSD. For LSD modelling and projection, we first evaluated two temperature-driven LSD models [i.e., cooling-degree-day (CDD, without DTR effect) and day–night-temperature CDD (DN_CDD, with DTR effect)], then applied them to predict future LSDs.

Results

We found that observational increases in T_mean and DTR had contrasting effects on LSD. Increased T_mean delayed the LSD, whereas larger DTR overall had an advancing effect. Considering the DTR effect, the T_mean sensitivity of LSD was 14% lower than presently estimated (2.4 vs. 2.8 days °C⁻¹). Warming asymmetry-related drought stress and plant functional traits (i.e., plant isohydricity and water-use efficiency) potentially explained the advancing effect of DTR on LSD. We found that current projections of future LSD are overestimated because the DTR effect is discounted, suggesting the need for an adequate understanding of how plant phenology responds to warming asymmetry.

Main conclusions

Our findings highlight the importance of DTR in controlling LSD variations with an advancing-dominant effect and call for the improvement of phenology modelling incorporating the DTR effect. Given that DTR showed a globally narrowing trend over the last several decades, more efforts are needed to understand the potential ecological impacts of warming asymmetry and vegetation response to climate change.     

中国北方农牧交错带生态系统服务空间格局及影响因子——以内蒙古中西部地区为例

中国北方农牧交错带是我国重要的生态安全屏障之一,面临经济发展与脆弱生态环境保护间的突出矛盾。生态系统服务的定量研究是生态可持续管理的重要科学依据,也是当前的研究热点之一。以北方农牧交错带的核心区域--内蒙古中西部地区为例,结合中高分辨率遥感数据和生物物理模型准确量化了2000-2018年关键生态系统服务,基于Getis-Ord G^*方法分析了生态系统服务的空间格局,考虑地理数据的空间自相关性选取了空间回归模型探索其影响因子。结果表明：（1）净初级生产力（NPP,Net primary productivity）、土壤水蚀控制服务（SC,Soil conservation）、产水量（WY,Water yield）及三层土壤含水量（SM1,Soil moisture of top layer;SM2,Soil moisture of middle layer;SM3,Soil moisture of bottom layer）在东部较高,防风固沙服务（SF,Sand fixation）在南部和西部较高;（2）以上生态系统服务受气候变化、景观格局、地形和土壤条件等综合影响,不同影响因素对生态系统服务的作用存在差异。NPP受森林景观格局和归一化植被指数的影响最为显著;WY、SM1、SM2、SM3及SC受降水量的影响较为显著;风速和表层土壤砂粒含量对SF影响最为显著。研究结果可以为优化景观格局和土地系统,缓解中国北方农牧交错带的社会-生态矛盾提供科学依据和案例参考。     

气候变化情景下祁连圆柏在青海省的适宜分布区预测

祁连圆柏具有良好的水土保持功能,是青海省高寒干旱地区造林绿化的优良乡土树种之一,预测未来气候变化情景下祁连圆柏在青海省的潜在地理分布将为祁连圆柏的经营管理和引种栽培提供理论指导。本研究基于实地调查和资料搜集获得88个有效地理分布样点,利用Maxent模型和ArcGIS空间分析技术对当前气候条件下祁连圆柏在青海省的潜在地理分布进行模拟,综合Jackknife检验和相关系数,分析影响祁连圆柏潜在分布的主导限制因子,同时结合第六次国际耦合模式比较计划(CMIP6)的气候模式数据,预测祁连圆柏在3种(SSP126、SSP245、SSP585)气候变化情景下2061—2080年潜在适生区的变化。结果表明:Maxent模型受试者工作特征曲线下面积(AUC)都大于0.92,具有较好的预测能力。在当前气候条件下,祁连圆柏的适宜分布区主要位于青海省东部,总适宜区面积占比为11.2%,影响其地理分布的主导因子是海拔、年均降水量、极端最低温和坡度,累计贡献率为85.9%。未来3种气候情景对祁连圆柏适宜区的影响存在差异,SSP245气候情景的适宜区面积将会缩减,SSP126和SSP585气候情景下则会不同程度地扩张,SSP126气候情景的扩张最明显,其扩张区域主要位于泽库县、河南蒙古族自治县中北部和祁连县东南部地区。在未来3种气候情景下,祁连圆柏适宜分布区逐渐向高海拔地区迁移,但在经纬度方向分布变化较小,适宜区总体稳定。     

Seasonally different response of photosynthetic activity to daytime and night‐time warming in the Northern Hemisphere

Over the last century the Northern Hemisphere has experienced rapid climate warming, but this warming has not been evenly distributed seasonally, as well as diurnally. The implications of such seasonal and diurnal heterogeneous warming on regional and global vegetation photosynthetic activity, however, are still poorly understood. Here, we investigated for different seasons how photosynthetic activity of vegetation correlates with changes in seasonal daytime and night‐time temperature across the Northern Hemisphere (>30°N), using Normalized Difference Vegetation Index (NDVI) data from 1982 to 2011 obtained from the Advanced Very High Resolution Radiometer (AVHRR). Our analysis revealed some striking seasonal differences in the response of NDVI to changes in day‐ vs. night‐time temperatures. For instance, while higher daytime temperature (T_max) is generally associated with higher NDVI values across the boreal zone, the area exhibiting a statistically significant positive correlation between T_max and NDVI is much larger in spring (41% of area in boreal zone – total area 12.6 × 10⁶ km²) than in summer and autumn (14% and 9%, respectively). In contrast to the predominantly positive response of boreal ecosystems to changes in T_max, increases in T_max tended to negatively influence vegetation growth in temperate dry regions, particularly during summer. Changes in night‐time temperature (T_min) correlated negatively with autumnal NDVI in most of the Northern Hemisphere, but had a positive effect on spring and summer NDVI in most temperate regions (e.g., Central North America and Central Asia). Such divergent covariance between the photosynthetic activity of Northern Hemispheric vegetation and day‐ and night‐time temperature changes among different seasons and climate zones suggests a changing dominance of ecophysiological processes across time and space. Understanding the seasonally different responses of vegetation photosynthetic activity to diurnal temperature changes, which have not been captured by current land surface models, is important for improving the performance of next generation regional and global coupled vegetation‐climate models.     

Interannual variation in seasonal drivers of soil respiration in a semi-arid Rocky Mountain meadow

Semi-arid ecosystems with annual moisture inputs dominated by snowmelt cover much of the western United States, and a better understanding of their seasonal drivers of soil respiration is needed to predict consequences of climatic change on soil CO₂ efflux. We assessed the relative importance of temperature, moisture, and plant phenology on soil respiration during seasonal shifts between cold, wet winters and hot, dry summers in a Rocky Mountain meadow over 3.5 separate growing seasons. We found a consistent, unique pattern of seasonal hysteresis in the annual relationship between soil respiration and temperature, likely representative for this ecosystem type, and driven by (1) continued increase in soil T after summer senescence of vegetation, and (2) reduced soil respiration during cold, wet periods at the beginning versus end of the growing season. The timing of meadow senescence varied between years with amount of cold season precipitation, but on average occurred 45 days before soil temperature peaked in late-summer. Autumn soil respiration was greatest when substantial autumn precipitation events occurred early. Surface CO₂ efflux was temporarily decoupled from respiratory production during winter 2006/2007, due to effects of winter surface snow and ice on mediating the diffusion of CO₂ from deep soil horizons to the atmosphere. Upon melt of a capping surface ice layer, release of soil-stored CO₂ was determined to be 65 g C, or ~10 % of the total growing season soil respiration for that year. The shift between soil respiration sources arising from moisture-limited spring plant growth and autumn decomposition indicates that annual mineralization of soil carbon will be less dependent on projected changes in temperature than on future variations in amount and timing of precipitation for this site and similar semi-arid ecosystems.     

Rapid laboratory measurement of the temperature dependence of soil respiration and application to changes in three diverse soils through the year

Determining the temperature dependence of soil respiration is needed to test predictive models such as Arrhenius-like functions and macro-molecular rate theory (MMRT). We tested a method for rapid measurement of respiration using a temperature gradient block, cooled at one end (~2 °C) and heated at the other (~50 °C) that accommodated 44 tubes containing soil incubated at roughly 1 °C increments. Gas samples were taken after 5 h incubation and analysed for CO₂. The temperature gradient block allowed rapid assessment of temperature dependence of soil respiration with the precision needed to test models and explore existing theories of how temperature and moisture interact to control biochemical processes. Temperature response curves were well fitted by MMRT and allowed calculation of the temperature at which absolute temperature sensitivity was maximal (T_inf). We measured temperature response of three soils at seven moisture contents and showed that the absolute rate and sensitivity of respiration was partly dependent on adjusted moisture content. This result implied that comparisons between soils need to be made at a common moisture content. We also measured potential changes in the temperature dependence (and sensitivity) of respiration for three different soils collected at one site throughout a year. T_inf ranged from 43 to 51 °C for the three soils. T_inf and temperature sensitivity were not dependent on soil type collected but was partly dependent on time of year of collection. Temporal changes in temperature response suggested that the microbial communities may tune their metabolisms in response to changes in soil temperatures.     

How uncertainties in future climate change predictions translate into future terrestrial carbon fluxes

We forced a global terrestrial carbon cycle model by climate fields of 14 ocean and atmosphere general circulation models (OAGCMs) to simulate the response of terrestrial carbon pools and fluxes to climate change over the next century. These models participated in the second phase of the Coupled Model Intercomparison Project (CMIP2), where a 1% per year increase of atmospheric CO₂ was prescribed. We obtain a reduction in net land uptake because of climate change ranging between 1.4 and 5.7 Gt C yr^?1 at the time of atmospheric CO₂ doubling. Such a reduction in terrestrial carbon sinks is largely dominated by the response of tropical ecosystems, where soil water stress occurs. The uncertainty in the simulated land carbon cycle response is the consequence of discrepancies in land temperature and precipitation changes simulated by the OAGCMs. We use a statistical approach to assess the coherence of the land carbon fluxes response to climate change. The biospheric carbon fluxes and pools changes have a coherent response in the tropics, in the Mediterranean region and in high latitudes of the Northern Hemisphere. This is because of a good coherence of soil water content change in the first two regions and of temperature change in the high latitudes of the Northern Hemisphere. Then we evaluate the carbon uptake uncertainties to the assumptions on plant productivity sensitivity to atmospheric CO₂ and on decomposition rate sensitivity to temperature. We show that these uncertainties are on the same order of magnitude than the uncertainty because of climate change. Finally, we find that the OAGCMs having the largest climate sensitivities to CO₂ are the ones with the largest soil drying in the tropics, and therefore with the largest reduction of carbon uptake.     

西南喀斯特区坡耕地秸秆覆盖对土壤生态化学计量特征及产量的影响

土壤养分亏缺是限制作物生长的关键因素,同时也是制约作物产量的重要影响因子。为提高西南喀斯特区坡耕地土壤肥力和作物产量,于2018—2019年连续两年在贵州省黔西县开展了野外原位径流小区观测试验。通过该试验探讨不同秸秆覆盖率下土壤碳(C)、氮(N)、磷(P)、钾(K)含量及其生态化学计量特征,揭示不同秸秆覆盖率下土壤养分状况及土壤改良效果。共设6个秸秆覆盖梯度,玉米单作+秸秆覆盖(SM₀—SM₅,0,1111、2222、3889、5556,6944 kg/hm~2),其中SM₀为对照组(CK)。结果表明：(1)秸秆覆盖不同程度增加了土壤有机碳(SOC)、全氮(TN)及全磷(TP)含量,总体上随覆盖量的增加而增加,尤其是覆盖量较多的情况下(SM₄,SM₅),均显著高于对照(P<0.05),但两者之间差异不显著(P> 0.05),而全钾(TK)则随着覆盖量的增加而减少。(2)在高秸秆覆盖条件下(SM₄,SM₅),除了N∶P外,两...     

Predicting the impact of future climate changes and range-shifts of Indian hornbills (family: Bucerotidae)

Climate change influences species distribution and is regarded as a major threat to biodiversity. Hornbills (Family: Bucerotidae) are large tropical birds in Asia and Africa. They are seed dispersers known as forest farmers because they help maintain the ecological community structure by allowing forest regeneration. They are keystone species, and their presence in a forest implies a healthy ecosystem. Range shifts due to climate change is a serious threat because their long-term survival is already imperilled by anthropogenic disturbances. This study models the current and future potential climatic niches of eight of the nine hornbill species present in India. We used GBIF-mediated species presence records along with eight WorldClim V2.1 bioclimatic variables to model the current climatically suitable areas and projected it into the future (mid-century, i.e., 2041–60 and end of the century, i.e., 2081–2100) for different CMIP6 based Shared Socioeconomic Pathway (SSPs) (i.e., SSP126, SSP245, 370 and 585). Range shifts, centroid changes, and the impact of current land use practices for each of the eight species under various climatic conditions were also examined. The Area Under Curve (AUC) values for final models ranged between 0.736 and 0.994. Result indicates that majority of species' climatic niche shift is towards the west, followed by northwest and northern shifts. The species are expected to lose >40% of their suitable present climatic niche under the SSP 585 scenario in 2081–2100. Natural areas were found to be climatically suitable for hornbills throughout the study area, implying the merit of conserving their existing habitats. Our research provides detailed information on how the distribution of Indian Hornbills may change because of future climatic conditions. Detailed spatial and temporal distribution and range shift patterns will aid in a targeted approach for conserving hornbills and their habitat in a changing climate.     

Three‐dimensional change in temperature sensitivity of northern vegetation phenology

Understanding how the temperature sensitivity of phenology changes with three spatial dimensions (altitude, latitude, and longitude) is critical for the prediction of future phenological synchronization. Here we investigate the spatial pattern of temperature sensitivity of spring and autumn phenology with altitude, latitude, and longitude during 1982–2016 across mid‐ and high‐latitude Northern Hemisphere (north of 30°N). We find distinct spatial patterns of temperature sensitivity of spring phenology (hereafter “spring S_T”) among altitudinal, latitudinal, and longitudinal gradient. Spring S_T decreased with altitude mostly over eastern Europe, whereas the opposite occurs in eastern North America and the north China plain. Spring S_T decreased with latitude mainly in the boreal regions of North America, temperate Eurasia, and the arid/semi‐arid regions of Central Asia. This distribution may be related to the increased temperature variance, decreased precipitation, and radiation with latitude. Compared to spring S_T, the spatial pattern of temperature sensitivity of autumn phenology (hereafter “autumn S_T”) is more heterogeneous, only showing a clear spatial pattern of autumn S_T along the latitudinal gradient. Our results highlight the three‐dimensional view to understand the phenological response to climate change and provide new metrics for evaluating phenological models. Accordingly, establishing a dense, high‐quality three‐dimensional observation system of phenology data is necessary for enhancing our ability to both predict phenological changes under changing climatic conditions and to facilitate sustainable management of ecosystems.     

Multiscale analysis of temporal variability of soil CO2 production as influenced by weather and vegetation

Ecosystem processes are influenced by weather and climatic perturbations at multiple temporal scales with a large range of amplitudes and phases. Technological advances of automated biometeorological measurements provide the opportunity to apply spectral methods on continuous time series to identify differences in amplitudes and phases and relationships with weather variation. Here we used wavelet coherence analysis to study the temporal covariance between soil CO₂ production and soil temperature, soil moisture, and photosynthetically active radiation (PAR). Continuous (hourly average) data were acquired over 2 years among three vegetation types in a semiarid mixed temperate forest. We showed that soil temperature and soil moisture influence soil CO₂ production differently at multiple periods (e.g. hours, days, weeks, months, years), especially after rain pulse events. Our results provide information about the periodicity of soil CO₂ production among vegetation types, and provide insights about processes controlling CO₂ production through the study of phase relationships between two time series (e.g. soil CO₂ production and PAR). We tested the performance of empirical models of soil CO₂ production using the continuous wavelet transform. These models, built around soil temperature and moisture, failed at multiple periods across the measured dates, suggesting that empirical models should include other factors that regulate soil CO₂ production at different temporal scales. Our results add a new dimension for the analysis of continuous time series of biometeorological measurements and model testing, which will prove useful for analysis of increasing sensor data obtained by environmental networks.     

Carbon mineralization of Chinese fir (Cunninghamia lanceolata) soils under different temperature and humidity conditions

Burned and unburned mineral soils (0–10 cm) from a 40-year-old Chinese fir (Cunninghamia lanceolata) forest in Nanping, Fujian, China were incubated for 90 days at different temperatures (25 °C and 35 °C) and humidity [25%, 50%, and 75% of water holding capacity (WHC)] conditions. Carbon (C) mineralization of all soils was determined using CO₂ respiration method. The results showed that CO₂ evolution rates of the burned and control soils exhibited similar temporal patterns, and similar responses to temperature and moisture. CO₂ evolution rates for all soil samples decreased with incubation time. At different humidity conditions, average rate of C mineralization and cumulative mineralized C from burned and control soils were significantly higher at 35 °C than at 25 °C. This implied that C mineralization was less sensitive to soil moisture than to temperature. In both soils at 25 °C or 35 °C, the amount of soil evolved CO₂ over the 90 days incubation increased with increasing moisture content from 25% to 75% WHC. A temperature coefficient (Q₁₀) varied with soil moisture contents. The maximum values recorded for Q₁₀ were 1.7 in control soil and 1.6 in burned soil both at 25% WHC. However, there were no significant differences in Q₁₀ values between the control and burned soils over all moisture ranges (P > 0.05). The data of cumulative C–CO₂ released from control and burned soils were fitted to two different kinetic models. The two simultaneous reactions model described mineralization better than the first-order exponential model, which reflected the heterogeneity of substrate quality. Based on these results, it is possible to conclude that temperature and moisture are important in the controls of C mineralization, and the combined effects of these variables need to be considered to understand and predict the response of CO₂ release in subtropical ecosystems to climate change.     

基于MaxEnt模型的云南干热河谷适生树种选择

基于MaxEnt模型识别和预测云南干热河谷适生树种,对于改善和恢复其生态治理能力具有重要意义。收集40种具有代表性的潜在适生树种地理分布数据,结合气候、地形和土壤等环境因子,利用MaxEnt模型筛选适生树种。预测当前和2021-2040年四种气候情景下(SSP126、SSP245、SSP370和SSP585)适生树种适生区的分布格局,划分优先种植区域,并明确MaxEnt模型用于树种选择的可行性。结果表明:(1)当前气候情景下,影响干热河谷潜在适生树种分布的主导因子是气候因子,其次是海拔、植物归一化指数、地表太阳辐射量和人类足迹。(2)未来,24种适生树种适生区稳定,发生概率与海拔关系呈单峰分布且高海拔下适生树种丰富度将降低。(3)干热河谷适生树种优先种植区域沿干热河谷呈狭长分布;实际调查发现,元谋县适生树种实际分布区域面积略高于最佳种植区域面积。应用MaxEnt模型筛选干热河谷适生树种选择是可行的,但在应用之前必须通过实地调查来验证树种实际生存情况与预测结果的差异。在干热河谷生态修复造林时,可优先考虑白枪杆、车桑子等24种树种。     

Large seasonal changes in Q10 of soil respiration in a beech forest

We analyzed one year of continuous soil respiration measurements to assess variations in the temperature sensitivity of soil respiration at a Danish beech forest. A single temperature function derived from all measurements across the year (Q₁₀ = 4.2) was adequate for estimating the total annual soil respiration and its seasonal evolution. However, Q₁₀'s derived from weekly datasets ranged between three in summer (at a mean soil temperature of 14 °C) and 23 in winter (at 2 °C), indicating that the annual temperature function underestimated the synoptic variations in soil respiration during winter. These results highlight that empirical models should be parameterized at a time resolution similar to that required by the output of the model. If the objective of the model is to simulate the total annual soil respiration rate, annual parameterization suffices. If however, soil respiration needs to be simulated over time periods from days to weeks, as is the case when soil respiration is compared to total ecosystem respiration during synoptic weather patterns, more short‐term parameterization is required. Despite the higher wintertime Q₁₀'s, the absolute response of soil respiration to temperature was smaller in winter than in summer. This is mainly because in absolute numbers, the temperature sensitivity of soil respiration depends not only on Q₁₀, but also on the rate of soil respiration, which is highly reduced in winter. Nonetheless, the Q₁₀ of soil respiration in winter was larger than can be explained by the decreasing respiration rate only. Because the seasonal changes in Q₁₀ were negatively correlated with temperature and positively correlated with soil moisture, they could also be related to changing temperature and/or soil moisture conditions.     

Phenophases alter the soil respiration–temperature relationship in an oak-dominated forest

Soil respiration (SR) represents a major component of forest ecosystem respiration and is influenced seasonally by environmental factors such as temperature, soil moisture, root respiration, and litter fall. Changes in these environmental factors correspond with shifts in plant phenology. In this study, we examined the relationship between canopy phenophases (pre-growth, growth, pre-dormancy, and dormancy) and SR sensitivity to changes in soil temperature (T_S). SR was measured 53 times over 550 days within an oak forest in northwest Ohio, USA. Annual estimates of SR were calculated with a Q₁₀ model based on T_S on a phenological (PT), or annual timescale (AT), or T_S and soil volumetric water content (VWC) on a phenological (PTM) or annual (ATM) timescale. We found significant (p<0.01) difference in apparent Q₁₀ from year 2004 (1.23) and year 2005 (2.76) during the growth phenophase. Accounting for moisture-sensitivity increased model performance compared to temperature-only models: the error was −17% for the ATM model and −6% for the PTM model. The annual models consistently underestimated SR in summer and overestimated it in winter. These biases were reduced by delineating SR by tree phenophases and accounting for variation in soil moisture. Even though the bias of annual models in winter SR was small in absolute scale, the relative error was about 91%, and may thus have significant implications for regional and continental C balance estimates.     

气候变化对祁连山蒙古扁桃潜在适生区的影响

气候变化将改变物种的生存环境,影响其分布范围,甚至威胁到某些物种的生存。本文通过ArcGIS软件和最大熵(MaxEnt)模型模拟蒙古扁桃(Amygdalus mongolica)在祁连山当前(1970—2000年)和未来(2081—2100年)2个气候时期背景下的地理分布格局,并分析其主要的环境影响因素。结果表明：(1)在当前气候条件下,蒙古扁桃在祁连山的东南部有较好的适生性;(2)未来4种气候情景下(SSP126,SSP245,SSP245和SSP585),蒙古扁桃在祁连山南部及东南部的适生区有消失的风险,扩张区主要集中在祁连山中北部的国家公园附近;(3)蒙古扁桃的分布格局主要向祁连山北部和高纬度地区迁移;(4)最湿月降水量(Bio13)、坡度(Slope)、最冷季度均温(Bio11)和最热月最高温(Bio5)的累计贡献率达到了80%以上,是影响蒙古扁桃适生分布的主要因子。本研究模拟、分析、预测了当前和未来不同情景下蒙古扁桃在祁连山的潜在分布及其变化,为祁连山生态及物种多样性的保护提供科学依据。     

Soil N and C trace gas fluxes and microbial soil N turnover in a sessile oak (Quercus petraea (Matt.) Liebl.) forest in Hungary

During two intensive field campaigns in summer and autumn 2004 nitrogen (N₂O, NO/NO₂) and carbon (CO₂, CH₄) trace gas exchange between soil and the atmosphere was measured in a sessile oak (Quercus petraea (Matt.) Liebl.) forest in Hungary. The climate can be described as continental temperate. Fluxes were measured with a fully automatic measuring system allowing for high temporal resolution. Mean N₂O emission rates were 1.5 μg N m⁻² h⁻¹ in summer and 3.4 μg N m⁻² h⁻¹ in autumn, respectively. Also mean NO emission rates were higher in autumn (8.4 μg N m⁻² h⁻¹) as compared to summer (6.0 μg N m⁻² h⁻¹). However, as NO₂ deposition rates continuously exceeded NO emission rates (−9.7 μg N m⁻² h⁻¹ in summer and −18.3 μg N m⁻² h⁻¹ in autumn), the forest soil always acted as a net NO _x sink. The mean value of CO₂ fluxes showed only little seasonal differences between summer (81.1 mg C m⁻² h⁻¹) and autumn (74.2 mg C m⁻² h⁻¹) measurements, likewise CH₄uptake (summer: −52.6 μg C m⁻² h⁻¹; autumn: −56.5 μg C m⁻² h⁻¹). In addition, the microbial soil processes net/gross N mineralization, net/gross nitrification and heterotrophic soil respiration as well as inorganic soil nitrogen concentrations and N₂O/CH₄ soil air concentrations in different soil depths were determined. The respiratory quotient (ΔCO_{2 resp} ΔO_{2 resp}⁻¹) for the uppermost mineral soil, which is needed for the calculation of gross nitrification via the Barometric Process Separation (BaPS) technique, was 0.8978 ± 0.008. The mean value of gross nitrification rates showed only little seasonal differences between summer (0.99 μg N kg⁻¹ SDW d⁻¹) and autumn measurements (0.89 μg N kg⁻¹ SDW d⁻¹). Gross rates of N mineralization were highest in the organic layer (20.1–137.9 μg N kg⁻¹ SDW d⁻¹) and significantly lower in the uppermost mineral layer (1.3–2.9 μg N kg⁻¹ SDW d⁻¹). Only for the organic layer seasonality in gross N mineralization rates could be demonstrated, with highest mean values in autumn, most likely caused by fresh litter decomposition. Gross mineralization rates of the organic layer were positively correlated with N₂O emissions and negatively correlated with CH₄ uptake, whereas soil CO₂ emissions were positively correlated with heterotrophic respiration in the uppermost mineral soil layer. The most important abiotic factor influencing C and N trace gas fluxes was soil moisture, while the influence of soil temperature on trace gas exchange rates was high only in autumn.     

百年尺度地球系统模式模拟的陆地生态系统碳通量对CO2浓度升高和气候变化的响应

利用了加拿大地球系统模式CanE SM2(Canadian Earth System Model of the CCCma)的结果,针对百年尺度大气CO_2浓度升高和气候变化如何影响陆地生态系统碳通量这一问题,分析了1850—1989年间陆地生态系统碳通量趋势对二者响应,以及与关键气候系统变量的关系。结果表明,140年间,当仅仅考虑CO_2浓度升高影响时,陆地生态系统净初级生产力(NPP)增加了117.1 gC m~(-2)a~(-1),土壤呼吸(Rh)增加了98.4 gC m~(-2)a~(-1),净生态系统生产力(NEP)平均增加了18.7 gC m~(-2)a~(-1)。相同情景下,全球陆地生态系统的NPP呈显著增加的线性趋势(约为0.30 PgC/a~2),Rh同样呈显著增加线性趋势(约为0.25 PgC/a~2)。仅仅考虑气候变化单独影响时,NPP平均减少了19.3 gC/m~2,土壤呼吸减少了8.5 gC/m~2,NEP减少了10.8 gC/m~2。在此情景下,整个陆地生态系统的NPP线性变化趋势约为-0.07 PgC/a~2(P0.05),Rh线性变化趋势约为-0.04 PgC/a~2(P0.05)。综合二者的影响,前者是决定陆地生态系统碳通量变化幅度和空间分布的最重要影响因子,其影响明显大于气候变化。值得注意的是,CanE SM2并没有考虑氮素的限制作用,所以CO_2浓度升高对植被的助长作用可能被高估。此外,气候变化的贡献也不容忽视,特别是在亚马逊流域,由于当温度升高、降水和土壤湿度减少,NPP和Rh均呈显著减少趋势。     

Soil Mapping in the Pantanal of Mato Grosso, Brazil, using Multitemporal Landsat TM data

Keywords Multitemporal data sets from the Landsat Thematic Mapper (TM) were used to evaluate their applicability for exploratory soil mapping in the floodplain of the Northern Pantanal of Mato Grosso, Brazil. Fifty-four soil profiles were classified into 21 soil units according to the FAO–UNESCO system. Information layers of vegetation types and dynamics of flooding were elaborated by applying supervised hierarchical classification rules. Geomorphologic units were mapped by visual image interpretation. Multinomial logistic regression was applied to test relations between thematic layers and soil units as well as aggregated soil clusters, developing a statistical mapping model. Northern Pantanal floodplain soils show a high variability as a function of age and granulemetry of underlying sediments, as well as soil moisture and flooding regimes. GIS layers of nine vegetation formations, three geomorphologic units and three multi-temporal moisture types were elaborated. Cross-tabulations and multinomial logistic regression models indicate significant relations between FAO–UNESCO soil units and GIS layers. As soil sampling density had been low, a final predictive model was developed for the mapping of six aggregated soil clusters, obtaining a high significance level (p<0.05) for prediction. Applied methodology was found to be appropriate to develop models on soil–landscape relationships and improve information on spatial distribution of soil groupings in the Northern Pantanal.     

Temporal patterns of soil CO2 efflux in a temperate Korean Larch (Larix olgensis Herry.) plantation, Northeast China

There is little information available regarding seasonal and annual variations in soil CO₂ efflux from Korean Larch plantations, which are an important component of forests’ carbon balance in temperate China. In this study, the soil respiration rate (R _s), soil temperature (T ₁₀) and soil moisture (SM₁₀) at 10 cm depth were observed in a Korean Larch (Larix olgensis Herry.) plantation in Northeast China from 2008 to 2012. Mean R _s in growing season (GS) varied greatly, ranged from 2.32 ± 0.08 to 3.88 ± 0.09 μmol CO₂ m^?2 s^?1 (mean ± SE) over the period of 2008–2012. In comparison with T-model, the increase of explained variability by applying both T ₁₀ and SM₁₀ to the T-M model is very small. It is indicated that R _s was controlled largely by T ₁₀ in the present study. By accounting for 22.2 and 17.7 % of the total soil CO₂ emissions in 2010/2011 and 2011/2012, respectively, the soil CO₂ efflux in dormant season (DS) was an essential component of the total soil CO₂ efflux. The Q ₁₀ value in the study period was always smaller for GS than DS, suggesting that soil carbon cycling may be more sensitive to the temperature changes at low than at high temperature range. These results indicated that climate changes may have great potential impacts on temperate Larch plantations in Northeast China, owing to soil carbon emissions of Larch plantation during the long period of DS being more sensitive to T ₁₀ than in GS, and played a significant role in the annual forest ecosystems carbon budget.