Pre-growing Season Research Articles

Comparative Analysis of Drought Effects on the Soil Moisture Level and Penetration Resistance in Conventional and Non-Conventional Tillage Systems in Maize Production

The period of extreme weather anomalies in recent years has challenged farmers, and this has encouraged greater adaptability in farming practices. In the last decade, conventional tillage systems have been complemented by more biologically based cropping systems. The research evaluated the impact of drought on soil physical parameters in maize production by testing different conventional and non-conventional tillage systems to ensure optimal soil physical parameters. In the analysis of the prevailing weather conditions, rainfall values were divided into two parts, the pre-growing season and the growing season. We studied different climatic seasons. In 2021, the soil moisture content in the upper shallow 15 cm soil layer during the sowing period in April in the case of conventional tillage was significantly lower than in reduced tillage, conservation tillage and strip tillage. The most significant difference was measured between conventional and conservation tillage, with a difference of 11.25 v/v%. The 2022 crop year was extremely dry. In June, the highest moisture value in the soil was measured in the case of strip tillage with a value of 21.64 v/v%, which was more than 60% higher than in the case of conventional and conservation tillage. In conventional tillage, a very pronounced compacted layer was observed in the lower part of the ploughed layer. This zone reached a compaction of 6.9 MPa between 28 and 34 cm, which is agronomically harmful. No compacted soil layer was found in the experiment site under conservation tillage. In the severe drought year of 2022, only the strip-till system provided the proper water management conditions for the maize stand.

Functional trait-based phytoplankton biomass and assemblage analyses in the pre-growing season for comprehensive algal bloom risk assessment

Algal bloom (AB) risk assessment is critical for maintaining ecosystem health and human sustainability. Previous AB risk assessments have focused on the potential occurrence of ABs and related factors in the growing season, whereas their hazards, especially in the pre-growing season, have attracted less attention. Here, we performed a comprehensive AB risk assessment, including water trophic levels, phytoplankton biomass, functional trait-based assemblages, and related environmental factors, in the pre-growing season in Dongting Lake, China. Although mesotrophic water and low phytoplankton biomass suggested low AB potential, toxic taxa, which constituted 13.28% of the phytoplankton biomass, indicated non-negligible AB hazards. NH4+ and water temperature were key factors affecting phytoplankton motility and toxicity. Our study establishes a new paradigm for quantitative AB risk assessment, including both potential AB occurrence and hazards. We emphasize the importance of phytoplankton functional traits for early AB warning and NH4+ reduction for AB control in the pre-growing season.

Rapid Warming Exacerbates Winter Drought Stress in Trees at High-Altitude Areas in Northeast China

Against the background of global warming, trees in high-latitude and high-altitude areas are more sensitive to rapid warming. Revealing the response patterns of trees at different altitudes to rapid warming in typical alpine mountain environments can help to predict the future distribution of forests in the region and the associated changes in the timberline. This study used tree-ring width data (band sampling) from Dahurian larch (Larix gmelinii Rupr.) along an altitudinal gradient (970–1409 m) on Oakley Mountain to establish 10 chronologies and to analyze the growth–climate response of larch to warming and altitudinal changes along a gradient. The results showed that before rapid warming, larch growth was strongly influenced mainly by precipitation in July–August, while after warming, the growth was controlled mainly by precipitation (snowfall) in winter (October–April) and showed a significant positive correlation with the SPEI in winter and a negative correlation with temperature in February–April (early spring). This indicates that the rapid warming event led to a drastic change in the water heat balance during the pre-growth period of the trees in the study area, which shifted the tree growth from being restricted by drought in the growing season before warming to being restricted by winter drought (i.e., the lagged effect of snowfall in the pre-growing season) after warming and that the trees at low altitudes suffered from more severe winter drought. In the future, as the global climate warms further, the growth of mountain larch at low altitudes (below 1200 m) will continue to decrease, and the coupling of winter snowfall and seasonal (February–April) warming will increase the upper altitude limit at which winter drought occurs for larch in the study area; additionally, larch at higher altitudes will be able to cope with this ecological process better.

Significant influences of extreme climate on autumn phenology in Central Asia grassland

Over the past half-century, there has been a significant rise in the frequency and intensity of extreme climate events in dryland ecosystems. While vegetation phenology acts as an important indicator of how ecosystems respond to climate change, the impact of extreme climate events on autumn phenology in dryland ecosystems remains uncertain. In this study, we firstly assessed the temporal variations in the end of growing season (EOS) in Central Asia using the Normalized Difference Vegetation Index and enhanced vegetation index over 2001–2018. Then, we assessed the impacts of eight climate indices, which capture the average and extreme conditions of the local climate, on EOS across diverse vegetation types using linear mixed models. Finally, we conducted partial correlation analysis to explore how the primary influencing factors affect EOS along an elevational gradient. Our results suggested increased occurrences of drought and heat events in the pre-growing season (April–September) in Central Asia. Under the background, a general trend towards earlier EOS (ca. 1.01 days/decade) was observed for grassland. This trend was mostly attributed to the changes in extreme climate indices (CIextreme), especially heavy rainfall and heat stress. The total explanatory power of CIextreme was almost twice that of mean climate indices (CImean). However, the impact of CIextreme was less pronounced in regions with elevations exceeding 1500 m. For forests and shrublands, the EOS exhibited delaying trend of 1.29 days/decade and advancing trend of 1.21 days/decade, respectively. Contrary to grasslands, the variations in EOS of forests and shrublands were largely influenced by the shift of CImean, especially mean minimum temperature and accumulated precipitation. The contribution of CIextreme accounted for only 1/6 of the contribution of CImean, likely attributed to the adaptation of forests to cold conditions and shrublands to arid conditions. The results provide valuable insights into the phenological response to extreme climate events and serve as a reference for ecosystem management in arid regions.

Asymmetric pre-growing season warming may jeopardize seed reproduction of the sand-stabilizing shrub Caragana microphylla

Our current understanding of the processes and mechanisms by which seasonal asymmetric warming affects seed reproduction in semiarid regions, which are essential in preserving the stability of both vegetation ecosystem structure and function, remains poorly understood. Here, we conducted a field warming experiment, including pre-growing season warming (W1), in-growing season warming (W2), and combined pre- and in-growing season warming (W3) treatments, to investigate the seed reproductive strategy of Caragana microphylla, an important sand-stabilizing shrub, from the perspective of reproductive phenology, reproductive effort, and reproductive success. Results show that the warming treatments advanced the initial stages of reproductive phenology, prolonged its duration, and decreased its synchrony (magnitude = W3 > W2 > W1). Additionally, flowering phenology was more sensitive to warming than podding phenology. The W1 treatment inclined seed reproduction towards the conservative strategy with low reproductive effort and success. The W3 treatment tended to increase seed reproductive effort and success. While the W2 treatment did not affect reproductive success, it did increase reproductive effort. Changes in reproductive phenology explained 20 % of the variation in reproductive effort and 38 % of the variation in reproductive success. However, these changes also directly hindered reproductive success (direct effect = −0.57) while indirectly promoting reproductive success (indirect effect = 0.27) by increasing reproductive efforts. Our results reveal that the seasonal asymmetry of warming altered the seed reproduction strategy of sand-stabilizing shrubs, with warmer winters and springs before the growing season decreasing seed fecundity.

Elevation Gradients Limit the Antiphase Trend in Vegetation and Its Climate Response in Arid Central Asia

Vegetation in arid central Asia (ACA) has been experiencing significant changes due to substantial warming and humidification since the 1980s. These changes are inhomogeneous due to the ecological vulnerability and topographic complexity of ACA. However, the heterogeneity of vegetation changes has received limited attention in the literature, which has focused more on the region’s overall general features. Thus, this paper analyzes the regional heterogeneity of vegetation changes during the growing season in ACA and further explores their underlying drivers. The results reveal an antiphase trend of vegetation, with an increase in eastern ACA and a decrease in western ACA. This antiphase pattern is primarily constrained by the divergent hydrothermal and climatic contexts of different elevation gradients. At elevations higher than 300 m (in the eastern ACA), increased growing season precipitation dominates vegetation greening. Conversely, vegetation at elevations lower than 300 m (in western ACA) is influenced by growing season soil water, which is driven by winter precipitation (pre-growing season precipitation). Additionally, the temperature could indirectly impact vegetation trends by altering precipitation, soil water, glaciers, snow cover, and runoff. Our findings have implications for restoring the ecosystem and sustainable development in ACA.

Dynamic responses of tree-ring growth to drought over Loess Plateau in the past three decades

Since the 1990s, global warming has substantially affected the dynamic responses of forest ecosystems to drought by altering tree growth and ecosystems carbon cycling. The Loess Plateau is a typical vegetation recovery region with an arid and semiarid climate. However, the responses of the vegetation in this region to drought have not been fully studied. We therefore aimed to characterize these responses in tree-ring samples, which were obtained by drilling tree cores with a growth cone, for establishing the tree-ring width chronologies. In addition, we investigated the main factors controlling the radial growth of Chinese pine (Pinus tabulaeformis) and its dynamic responses to drought in the Loess Plateau using correlation analysis. Our results show that radial growth in Chinese pine had a positive correlation with precipitation during the last growing season, pre-growing season, and entire current growing season. The correlation between the radial growth and temperature was inconsistent between different sampling sites and time periods. These suggest that precipitation was more likely to affect radial vegetation growth than temperature. Moreover, the drought indices calculated using data before the year 2000 more accurately reflected the vegetation drought situation in Loess Plateau than data from the last 20 years. The drier the place, the more accurately the drought indices represented the responses of vegetation to drought. However, these indices cannot satisfactorily capture the drought responses of vegetation in wet regions. Furthermore, the PDSI was more accurate than the SPEI at capturing the effects of drought on radial vegetation growth. Understanding the response mechanism of the radial growth of Chinese pine to drought can provide theoretical support for ecological protection, forest management, and ecological construction under climate change.

Responses of radial growth of Juniperus przewalskii to different droughts over the northeastern Tibetan Plateau, China

To study the responses of radial growth of Juniperus przewalskii to climate factors of the different periods (pre-growing season (February-April), growing season (May-July)), and the vulnerability (resistance, RT; recovery, RC) of J. przewalskii to different drought events (precipitation, temperature and the both caused), we used tree ring width data of J. przewalskii from 17 sampling sites across the northeastern Tibetan Plateau to analyze the correlation between radial growth and climate factors of different periods, and the vulnerability in different drought events. The results showed that radial growth of J. przewalskii had significant positive correlation with drought index and negative correlation with temperature in the growing season (P<0.1). The vulnerability of J. przewalskii to drought events of different periods had significant difference. In the pre-growing season drought events, the RT of J. przewalskii at low altitude was 2.3% higher than that at high altitude, the RC of J. przewalskii at low altitude was 25.1% lower than that at high altitude. For drought events in the growing season, the RT of J. przewalskii at low altitude was 23.7% lower than that at high altitude, the RC of J. przewalskii at low altitude was 107.1% higher than that at high altitude. The mean RC(1.68) of J. przewalskii in precipitation-caused drought events was strong, while the mean RT(1.43) of J. przewalskii in temperature-caused drought events was strong. The growth of J. przewalskii, especially for that at low altitude, would be largely limited by drought caused by global warming in the future.

Dissolved nitrogen exports from watersheds with contrasting land uses in sub-humid cool-temperate climates

Knowledge is limited in responses of watershed dissolved nitrogen (N) export to different land uses in Baijiang soil area under sub-humid cool-temperate climates. This study provided comparisons of three adjacent sub-watersheds (SWs) with contrasting land uses (SW 1: mixed land uses of woodland, dry cropland and residential area; SW 2: dry cropland dominated; and SW 3: paddy field dominated) after agricultural land use conversion (from woodland to dry cropland at SW 1 and SW 2 and from dry cropland to paddy field at SW 3) at the Abujiao River watershed, NE China. Exports of total dissolved N (TN), nitrate N (NO3-N) and ammonium N (NH4-N) in base and storm flows during the pre-growing, growing and post-growing seasons were investigated. Water discharge at the sub-watersheds mainly occurred as base flow with mean base flow index ranging within 0.62 – 0.69, while base flow and storm flow N exports were comparable. Across sub-watersheds, TN, NO3-N and NH4-N exported equally through base flow (1.36 – 3.16, 0.56 – 1.69 and 0.24 – 0.63 kg km−2 d−1, respectively) and storm flow (1.42 – 2.95, 0.54 – 1.66 and 0.42 – 0.63 kg km−2 d−1, respectively). SW 3 presented greater N export than SW 1 and SW 2 through base flow in the pre-growing (3.49 – 3.55, 3.21 – 4.30 and 3.27 – 4.47 times for TN, NO3-N and NH4-N, respectively) and growing seasons (1.95 – 3.32, 2.34 – 2.62 and 1.94 – 2.46 times for TN, NO3-N and NH4-N, respectively) and through storm flow in the pre-growing season (2.73 – 3.97, 2.59 – 4.02 and 3.38 – 4.00 times for TN, NO3-N and NH4-N, respectively). No significant difference in N export were found between SW 1 and SW 2. This study suggested special emphasis on the increased export of dissolved N through base flow and storm flow after dry croplands were converted to paddy fields.

Timing and Order of Extreme Drought and Wetness Determine Bioclimatic Sensitivity of Tree Growth

AbstractTree resistance to extreme droughts and post‐drought recovery are sensitive to the drought timing. However, how the bioclimatic sensitivity of tree growth may vary with the timing and order of extreme droughts and wetness is still poorly understood. Here, we quantified the bioclimatic sensitivity of tree growth in the period of 1951–2013 under different seasonal extreme drought/wetness regimes over the extra‐tropical Northern Hemisphere, using 1,032 tree ring chronologies from 121 gymnosperm and angiosperm species. We found a negative asymmetry in tree growth under regimes with seasonal extreme droughts. With extreme drought, tree growth in arid and temperate dry regions is more negatively impacted by pre‐growing‐season (PGS) extreme droughts. Clade‐wise, angiosperms are more sensitive to PGS water availability, and gymnosperms to legacy effects of the preceding tree growth conditions in temperate dry and humid regions. Our finding of divergent bioclimatic legacy effects underscores contrasting trends in forest responses to drought across different ecoregions and functional groups in a more extreme climate.

Diverse chronic responses of vegetation aboveground net primary productivity to climatic changes on Three-River Headwaters region

The ecological responses of vegetation to climatic variables along a spatial gradient can be used as guidelines for chronic ecosystem response predictions under global climate change. The chronic responses of aboveground net primary productivity (ANPP) to climatic factors on the Three-river Headwaters (TRH) region were assessed for major vegetation types at the herbage developmental stages using the geographical detectors model, the Normalized Difference Vegetation Index from remote sensing images, and precipitation and air temperature datasets from 2000 to 2019. The results indicated that precipitation was the dominant driver for alpine meadows and steppes, while the impact of temperature on alpine steppes was more evident than that in alpine meadows, and alpine shrubs were more responsive to warming changes. This was possibly because shallower root systems and larger plant leaf area promote the responses of ANPP to precipitation for alpine meadows and steppes, and dormant buds higher from the ground facilitate the impacts of temperature for alpine shrubs. Grasslands also demonstrated differentiated responses to climatic factors at different developmental stages. Precipitation during the previous withering (September–October), pre-growing season (March–April), and vegetative growth (May–June) stages were more influential for ANPP variations. In contrast, ANPP during the reproductive period from July to August exhibited a weaker response to climatic controls. This was possibly attributed to the bud bank replenishment in fall and spring, the largest biomass growth rates in vegetative growth stage, and the non-structural carbohydrates transferred from roots in reproductive stage for perennial herbaceous plants. An elevated temperature, combined with no significant change in precipitation on the TRH may lead to a decrease in ANPP in alpine meadows but alpine shrub expansion, resulting in a reduced supply of palatable forage sources and bringing challenges to grassland management.

Lateral detrital C transfer across a Spartina alterniflora invaded estuarine wetland

BackgroundThe lateral movements of mass and energy across the terrestrial-aquatic interface are being increasingly recognized for their importance in the carbon (C) balance of coastal/estuarine wetlands. We quantified the lateral flux of detrital C in the Yangtze estuary where invasive Spartina alterniflora has substantially and extensively altered the ecosystem structure and functions. Our overall objective was to close the C budget of estuarine wetlands through field sampling, tower-based measurements, and modeling.MethodsA lateral detrital C exchange evaluation platform was established in a case study of the Yangtze River Estuary to investigate the effect of ecosystem structural changes on lateral detrital C transfer processes. This study estimated the lateral detrital C exchange based on the gross primary production (GPP) by performing coupled modeling and field sampling. Tower-based measurements and MODIS time series and CH4 outgassing and biomass simultaneously measured the lateral detrital C flux to characterize the relative contributions of lateral (i.e., detritus) C fluxes to the annual marsh C budget.ResultsThe C pools in the plants and soil of Spartina marshes were significantly higher than those of the native community dominated by Phragmites australis. The GPP based on MODIS (GPPMODIS) was 472.6 g C m−2 year−1 and accounted for 73.0% of the GPP estimated from eddy covariance towers (GPPEC) (646.9 ± 70.7 g C m−2 year−1). We also detected a higher GPPMODIS during the pre-growing season, which exhibited a similar lateral detrital C flux magnitude. On average, 25.8% of the net primary production (NPP), which ranged from 0.21 to 0.30 kg C m−2 year−1, was exported during lateral exchange. The annual C loss as CH4 was estimated to be 17.9 ± 3.7 g C m−2 year−1, accounting for 2.8% of the GPPEC. The net positive detrital C flux (i.e., more detritus leaving the wetlands), which could exceed 0.16 kg C m−2 day−1, was related to daily tides. However, the observed lateral detrital C flux based on monthly sampling was 73.5% higher than that based on daily sampling (i.e., the sum of daily sampling), particularly in March and October. In addition, spatiotemporal granularities were responsible for most of the uncertainty in the lateral detrital C exchange.ConclusionThis research demonstrated that an integrated framework incorporating modeling and field sampling can quantitatively assess lateral detrital C transport processes across the terrestrial-aquatic interface in estuarine wetlands. However, we note some limitations in the application of the light-use efficiency model to tidal wetlands. Spartina invasion can turn the lateral C balance from a C source (209.0 g C m−2 year−1) of Phragmites-dominated marshes into a small C sink (-31.0 g C m−2 year−1). Sampling over a more extended period and continuous measurements are essential for determining the contribution of different lateral detrital C flux processes to closing the ecosystem C budgets. The sampling spatiotemporal granularities can be key to assessing lateral detrital C transfer.

Citizen scientists record novel leaf phenology of invasive shrubs in eastern U.S. forests

Invasive shrubs are an emergent concern in deciduous forests of eastern North America. Their extended leaf phenology (ELP)—earlier leaf emergence and later leaf off compared to native shrubs and the overstory canopy—can simultaneously provide photosynthetic benefits to invasive shrubs while negatively affecting native flora and fauna through producing novel understory shade when the overstory canopy is leafless. However, phenology varies geographically, and the degree to which ELP from local-scale studies applies across the range of forests experiencing shrub invasion is unknown. In partnership with the USA National Phenology Network, we developed a citizen science campaign to record broad patterns of species-specific ELP—an otherwise prohibitively large effort. Using 1500 observations of 14 species spanning 4 years, we found that the difference in leaf phenology between native and invasive shrubs can exceed 77 days within a growing season, a gap that decreases with increasing latitude by 2.9 [1.6, 4.2] days per degree latitude in the spring, and 2.2 [0.6, 1.9] in the fall. Geographic trends in ELP provide a context for interpreting local scale phenology research while bridging inconsistent findings between existing studies and can streamline management by targeting detection and removal of invasive shrubs with leaves while natives are dormant. Furthermore, even small changes to seasonal phenology can impact forest communities, especially if there is a differential response to climate cues by nativity. After exploring broad-scale environmental variables associated with leaf phenology, we find a similar correlation with pre-growing season warmth for native and invasive shrubs, but a different relationship with dormant chill days—a variable less frequently considered for modeling spring phenology for forest productivity.

Radial growth response of Pinus yunnanensis to rising temperature and drought stress on the Yunnan Plateau, southwestern China

The relative influence of energy and water availability on tree growth at specific sites under warming conditions remains insufficiently understood on the Yunnan Plateau, which obstructs the rational selection and development of forest management measures in the context of climate change. In this study, a dendroecological investigation was conducted in four sites on the Yunnan Plateau to evaluate growth trends and climate responses of Pinus yunnanensis under warming and drought stress across cold-dry (CD), warm-humid (WH), warm (WR), and hot-dry (HD) zones. The effects of energy and water availability on the radial growth of P. yunnanensis varied in different sites and showed site-specific characteristics. The radial growth of P. yunnanensis in the CD zone benefited from rising temperatures, especially in the pre-growing season and core growing season. However the radial growth of P. yunnanensis in the WH zone was restricted by excess water in the core growing season. The radial growth of P. yunnanensis in the WR and HD zones became increasingly limited by temperature and drought stress, and the growth switched from responding to energy stress to moisture stress. The sensitivity of P. yunnanensis to climate factors in the warm-humid zone and humid seasons was relatively stable; in contrast, this species was vulnerable to warming and drought stress under harsh growth conditions and showed considerable instability. Intense warming in the future may cause a significant variation of tree growth response to climate. It would trigger a noticeable redistribution effect of energy and water availability on forest growth, which motivates assessments of climate-growth relationships, not only at large spatial scales, but also in specific sites. This research provides a basis for the adoption of effective forest management measures for specific sites according to their response characteristics associated with the distribution of climate drivers.

Retrospective research of rice blast development in Krasnodar region

Today, rice blast remains the most dangerous disease, therefore, along with breeding developments, it is necessary to study the dependence of the pathogen’s behavior on agroclimatic conditions. In addition, an understanding of the dynamics of blast development in the non-growing season is necessary. The studies conducted are aimed at establishing agroclimatic patterns that contribute to the development of the disease in the pre-growing and growing periods by analyzing the results of the implementation of the mathematical model. As a result of research, the dependence of the intensity of damage to rice crops on the intensity of environmental influences in the pre-growing season was established, which suggests that it is necessary to apply agrotechnological measures before sowing to reduce the phytosanitary load on plants and the environment.

Maize yield and nitrate loss prediction with machine learning algorithms

Pre-growing season prediction of crop production outcomes such as grain yields and nitrogen (N) losses can provide insights to farmers and agronomists to make decisions. Simulation crop models can assist in scenario planning, but their use is limited because of data requirements and long runtimes. Thus, there is a need for more computationally expedient approaches to scale up predictions. We evaluated the potential of four machine learning (ML) algorithms (LASSO Regression, Ridge Regression, random forests, Extreme Gradient Boosting, and their ensembles) as meta-models for a cropping systems simulator (APSIM) to inform future decision support tool development. We asked: (1) How well do ML meta-models predict maize yield and N losses using pre-season information? (2) How many data are needed to train ML algorithms to achieve acceptable predictions? (3) Which input data variables are most important for accurate prediction? And (4) do ensembles of ML meta-models improve prediction? The simulated dataset included more than three million data including genotype, environment and management scenarios. XGBoost was the most accurate ML model in predicting yields with a relative mean square error (RRMSE) of 13.5%, and Random forests most accurately predicted N loss at planting time, with a RRMSE of 54%. ML meta-models reasonably reproduced simulated maize yields using the information available at planting, but not N loss. They also differed in their sensitivities to the size of the training dataset. Across all ML models, yield prediction error decreased by 10%–40% as the training dataset increased from 0.5 to 1.8 million data points, whereas N loss prediction error showed no consistent pattern. ML models also differed in their sensitivities to input variables (weather, soil properties, management, initial conditions), thus depending on the data availability researchers may use a different ML model. Modest prediction improvements resulted from ML ensembles. These results can help accelerate progress in coupling simulation models and ML toward developing dynamic decision support tools for pre-season management.

川西亚高山五种主要森林类型凋落物组成及动态

PDF HTML阅读 XML下载 导出引用 引用提醒 川西亚高山五种主要森林类型凋落物组成及动态 DOI: 10.5846/stxb201710311948 作者: 作者单位: 中国林业科学研究院森林生态环境与保护研究所,河南大学生命科学学院,中国农业科学院农业环境与可持续发展研究所,国际竹藤中心,四川大学生命科学学院,中国林业科学研究院森林生态环境与保护研究所 作者简介: 通讯作者: 中图分类号: 基金项目: 国家自然科学基金项目（31770490，31370463） Litter composition and its dynamic in five main forest types in subalpine areas of west Sichuan, China Author: Affiliation: Key Laboratory of Forest Ecology and Environment,State Forestry Administration,Institute of Forest Ecology,Environment and Protection,Chinese Academy of Forestry,School of Life Sciences,Henan University,3、 Key Laboratory of Dryland Agriculture, Ministry of Agriculture, Institute of Environment and Sustainable Development in Agriculture, Chinese Academy of Agricultural Sciences,4、 Key Laboratory of Bamboo and Rattan, International Centre for Bamboo and Rattan, Beijing 100102, China,5、 Key Laboratory of Bio-resource and Eco-environment of Ministry of Education, College of Life Sciences, Sichuan University,Key Laboratory of Forest Ecology and Environment,State Forestry Administration,Institute of Forest Ecology,Environment and Protection,Chinese Academy of Forestry Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:利用连续收获法研究了川西亚高山老龄林（VF）、桦木林（BF）、次生针阔混交林（MF）、人工云杉林（AF）及高山栎灌丛（AO）5种主要森林类型的凋落物组成及其动态，目的在于探索不同恢复途径对森林凋落物组成和产量的影响。结果表明，5种森林类型的全年凋落产量大小依次为VF（4.32 t/hm2）、MF（4.10 t/hm2）、BF（3.52 t/hm2）、AO（3.01 t/hm2）、AF（2.34 t/hm2）。AF全年凋落量显著小于其他3种乔木森林类型（VF，BF，MF）（P < 0.05）。各森林类型的叶片年凋落量占总量比例均超过70%。VF、AF、AO均在生长前期（前一年10月至当年5月）达到最大凋落量2.41，1.29，1.63 t/hm2；BF、MF凋落产量在生长季后期（当年7月至10月）到达最大值，分别为1.34，1.80 t/hm2。常绿针叶树为主的VF、AF叶片凋落物样地间变异显著高于落叶阔叶树为主的BF、MF，表明其对立地条件的响应更为敏感。林分密度与胸高断面积组合因子更能反映凋落物特征。 Abstract:Litter composition was investigated for a whole year in five representative forest types:virgin forest (VF), secondary birch forest (BF), secondary coniferous and broad-leaved mixed forest (MF), artificial spruce forest (AF), and alpine oak (AO), in west Sichuan, in order to understand the litter dynamic and spatial variation among different restoration approaches. The annual litter production for VF, MF, BF, AO, and AF was 4.32, 4.10, 3.52, 3.01, and 2.34 t/hm2, respectively. Litter production was significantly lower in AF than that in the other three forest types (VF, BF, and MF). More than 70% of annual litter was leaf in all forest types. Litter production of VF, AF, and AO reached its peak value (2.41, 1.29, and 1.63 t/hm2, respectively) in the pre-growing season (previous October-May), while that for BF and MF achieved their maximum (1.34 and 1.80 t/hm2, respectively) in the late growing season (July-October). Spatial variation of leaf litter for VF and AF, both composed of evergreen coniferous species, was significantly greater than that for BF and MF, with more deciduous species. Spatial variation analysis indicated that sensitivity of litter production to stand condition was higher for evergreen coniferous forest (VF, AF) than that for deciduous forest. The combination of stand density and area at breast height was advantageous in evaluating litter production. 参考文献 相似文献 引证文献

Phenology-Based Residual Trend Analysis of MODIS-NDVI Time Series for Assessing Human-Induced Land Degradation.

Land degradation is a widespread environmental issue and an important factor in limiting sustainability. In this study, we aimed to improve the accuracy of monitoring human-induced land degradation by using phenological signal detection and residual trend analysis (RESTREND). We proposed an improved model for assessing land degradation named phenology-based RESTREND (P-RESTREND). This method quantifies the influence of precipitation on normalized difference vegetation index (NDVI) variation by using the bivariate linear regression between NDVI and precipitation in pre-growing season and growing season. The performances of RESTREND and P-RESTREND for discriminating land degradation caused by climate and human activities were compared based on vegetation-precipitation relationship. The test area is in Western Songnen Plain, Northeast China. It is a typical region with a large area of degraded drylands. The MODIS 8-day composite reflectance product and daily precipitation data during 2000–2015 were used. Our results showed that P-RESTREND was more effective in distinguishing different drivers of land degradation than the RESTREND. Degraded areas in the Songnen grasslands can be effectively detected by P-RESTREND. Therefore, this modified model can be regarded as a practical method for assessing human-induced land degradation.

The responses of dominant tree species to climate warming at the treeline on the eastern edge of the Tibetan Plateau

Tree growth at boreal/alpine treelines is generally expected to be stimulated by climate warming. However, tree growth has been shown to have changed insignificantly or reduced in numerous studies. Tree response to climate warming also varies among species in the same eco-region. The Tibetan Plateau has experienced rapid warming in the past several decades. It remains unknown how the dominant species in this region have responded to this warming, which is expected to significantly influence treeline dynamics. We obtained 288 tree cores from fir (Abies faxoniana and Abies squamata) and spruce (Picea purpurea and Picea baifouriana) at six treeline sites on the eastern edge of the Tibetan Plateau to detect their growth trends and climate responses. The results showed that the growth of fir did not change significantly at any site, whereas spruce growth increased, especially at the Songpan and Luhuo sites. The strong negative temperature or positive moisture controls of April on fir growth indicated spring drought stress. The radial growth of spruce was positively related to June and July temperature; at the Songpan and Luhuo sites, it was also positively related to the temperature from February to April. The results indicate that both pre-growing season temperature and growing season temperature accelerate spruce growth, whereas pre-growing season temperature causes drought stress to fir. The tree species composition at the alpine treeline on the eastern edge of the Tibetan Plateau will change as warming continues.

Species- and Elevation-Dependent Growth Responses to Climate Warming of Mountain Forests in the Qinling Mountains, Central China

Climate warming is significantly affecting the composition and function of forest ecosystems. However, the forest responses to climate change in sub-humid and temperate areas are understudied compared with cold and semi-arid areas. Here, we investigate the radial-growth responses of two subalpine conifer species along an elevational gradient located in the Qinling Mountains, a sub-humid and temperate area situated in central China. Three sites dominated by larch (Larix chinensis Beissn.) and two other sites dominated by fir (Abies fargesii Franch.) located at different elevations were sampled. L. chinensis at a higher elevation showed more common and stronger climatic signals than A. fargesii at a lower elevation. The radial growth of L. chinensis was limited by low pre-growing season temperatures and showed an increasing growth trend in the last few years. On the other hand, A. fargesii growth was limited by summer water shortage and it was characterized by a declining trend in the most recent decade. Consequently, L. chinensis would benefit from climate warming, whereas A. fargesii could be regarded as a vulnerable tree species to warming-induced drought stress.