How biotic and abiotic factors affect stemflow production? Insights from both local and global scales

2020 ◽  
Author(s):  
Yafeng Zhang ◽  
Xinping Wang ◽  
Yanxia Pan ◽  
Rui Hu
Keyword(s):  
Abiotic Factors ◽  
Northern China ◽  
Boosted Regression Trees ◽  
Mean Annual Precipitation ◽  
Mean Annual Temperature ◽  
Abiotic Factor ◽  
Area Index ◽  
Biotic And Abiotic Factors ◽  
Vegetation Height ◽  
Caragana Korshinskii

<p>Stemflow production has been reported to be influenced by a suite of biotic and abiotic factors, and those factors would be quite different considering local and global scales. Although the number of published stemflow studies showed a steady increasing trend in recent years, the relative contributions of biotic and abiotic factors to stemflow production were still largely unclear due to the large number of influencing factors and the complex interactions among those factors. Here we present stemflow results conducted from both from local scale and global scale: (1) stemflow of nine xerophytic shrubs of Caragana korshinskii were measured in nearly nine growing seasons from 2010 to 2018 within a desert area of northern China, accompanying with observing on six biotic variables (shrub morphological attributes) and ten abiotic variables (meteorological conditions); (2) a global synthesis of stemflow production results (stemflow percentage was reported) derived from Web of Science for more than 200 peer-reviewed papers published in the last 50 years (1970-2019), and ten most reported biotic factors (vegetation life form, phenology, leaf form, bark form, community density, community age, vegetation height, diameter at breast height, leaf area index, stemflow measuring scale) and four abiotic factors (climate types, mean annual precipitation, elevation, mean annual temperature) were considered. We performed a machine learning method (boosted regression trees) to evaluate the relative contribution of each biotic and abiotic factor to stemflow percentage, and partial dependence plots were presented to visualize the effects of individual explanatory variables on stemflow percentage, respectively.</p>

scholarly journals Rule-based analysis of throughfall kinetic energy to evaluate biotic and abiotic factor thresholds to mitigate erosive power

2016 ◽  
Vol 40 (3) ◽  
pp. 431-449 ◽  
Author(s):  
Philipp Goebes ◽  
Karsten Schmidt ◽  
Werner Härdtle ◽  
Steffen Seitz ◽  
Felix Stumpf ◽  
...  
Keyword(s):  
Soil Erosion ◽  
Kinetic Energy ◽  
Leaf Area Index ◽  
Leaf Area ◽  
Abiotic Factors ◽  
Tree Height ◽  
Abiotic Factor ◽  
Area Index ◽  
Biotic And Abiotic Factors ◽  
Optimal Set

Below vegetation, throughfall kinetic energy (TKE) is an important factor to express the potential of rainfall to detach soil particles and thus for predicting soil erosion rates. TKE is affected by many biotic (e.g. tree height, leaf area index) and abiotic (e.g. throughfall amount) factors because of changes in rain drop size and velocity. However, studies modelling TKE with a high number of those factors are lacking. This study presents a new approach to model TKE. We used 20 biotic and abiotic factors to evaluate thresholds of those factors that can mitigate TKE and thus decrease soil erosion. Using these thresholds, an optimal set of biotic and abiotic factors was identified to minimize TKE. The model approach combined recursive feature elimination, random forest (RF) variable importance and classification and regression trees (CARTs). TKE was determined using 1405 splash cup measurements during five rainfall events in a subtropical Chinese tree plantation with five-year-old trees in 2013. Our results showed that leaf area, tree height, leaf area index and crown area are the most prominent vegetation traits to model TKE. To reduce TKE, the optimal set of biotic and abiotic factors was a leaf area lower than 6700 mm2, a tree height lower than 290 cm combined with a crown base height lower than 60 cm, a leaf area index smaller than 1, more than 47 branches per tree and using single tree species neighbourhoods. Rainfall characteristics, such as amount and duration, further classified high or low TKE. These findings are important for the establishment of forest plantations that aim to minimize soil erosion in young succession stages using TKE modelling.

Spatial Patterns and Drivers of Soil Chemical Properties in a Typical Hickory Plantation

2021 ◽  
Author(s):  
Mengjiao Sun ◽  
Enqing Hou ◽  
Jiasen Wu ◽  
Jianqin Huang ◽  
Xingzhao Huang
Keyword(s):  
Random Forest ◽  
Soil Nutrients ◽  
Spatial Patterns ◽  
Abiotic Factors ◽  
Soil Nutrient ◽  
Parent Material ◽  
Mean Annual Precipitation ◽  
Nutrient Concentrations ◽  
Available Phosphorus ◽  
Mean Annual Temperature

Abstract Background: Soil nutrients play critical roles in regulating and improving the sustainable development of economic forests. Consequently, an elucidation of the spatial patterns and drivers of soil nutrients in these forests is fundamental to their management. For this study, we collected 314 composite soils at a 0-30 cm depth from a typical hickory plantation in Lin 'an, Zhejiang Province, China. We determined the concentrations of macronutrients (i.e., soil organic carbon, hydrolyzed nitrogen, available phosphorus, and available potassium) and micronutrients (i.e., iron, manganese, zinc, and copper.) of the soils. We employed random forest analysis to quantify the relative importance of soil-forming factors to predict the soil nutrient concentrations, which could then be extrapolated to the entire hickory region. Results: Random forest models explained 61%–88% of the variations in soil nutrient concentrations. The mean annual temperature and mean annual precipitation were the most important predictor of soil macronutrient and micronutrient concentrations. Moreover, parent material was another key predictor of soil available phosphorus and micronutrient concentrations. Mapping results demonstrated the importance of climate in controlling the spatial distribution of soil nutrient concentrations at finer scales, as well as the effect of parent material, topography, stand structure, and management measures of hickory plantations. Conclusions: Our study highlights the biotic factors, abiotic factors, and management factors control over soil macronutrient and micronutrient concentrations, which have significant implications for the sustainability of soil nutrients in forest plantations.

scholarly journals Upside-down fluxes Down Under: CO<sub>2</sub> net sink in winter and net source in summer in a temperate evergreen broadleaf forest

2018 ◽  
Vol 15 (12) ◽  
pp. 3703-3716 ◽  
Author(s):  
Alexandre A. Renchon ◽  
Anne Griebel ◽  
Daniel Metzen ◽  
Christopher A. Williams ◽  
Belinda Medlyn ◽  
...  
Keyword(s):  
Large Scale ◽  
Vegetation Index ◽  
Ecosystem Respiration ◽  
Vapour Pressure Deficit ◽  
Summer Rainfall ◽  
Mean Annual Precipitation ◽  
Surface Conductance ◽  
Mean Annual Temperature ◽  
Eddy Covariance Method ◽  
Area Index

Abstract. Predicting the seasonal dynamics of ecosystem carbon fluxes is challenging in broadleaved evergreen forests because of their moderate climates and subtle changes in canopy phenology. We assessed the climatic and biotic drivers of the seasonality of net ecosystem–atmosphere CO2 exchange (NEE) of a eucalyptus-dominated forest near Sydney, Australia, using the eddy covariance method. The climate is characterised by a mean annual precipitation of 800 mm and a mean annual temperature of 18 ∘C, hot summers and mild winters, with highly variable precipitation. In the 4-year study, the ecosystem was a sink each year (−225 g C m−2 yr−1 on average, with a standard deviation of 108 g C m−2 yr−1); inter-annual variations were not related to meteorological conditions. Daily net C uptake was always detected during the cooler, drier winter months (June through August), while net C loss occurred during the warmer, wetter summer months (December through February). Gross primary productivity (GPP) seasonality was low, despite longer days with higher light intensity in summer, because vapour pressure deficit (D) and air temperature (Ta) restricted surface conductance during summer while winter temperatures were still high enough to support photosynthesis. Maximum GPP during ideal environmental conditions was significantly correlated with remotely sensed enhanced vegetation index (EVI; r2 = 0.46) and with canopy leaf area index (LAI; r2 = 0.29), which increased rapidly after mid-summer rainfall events. Ecosystem respiration (ER) was highest during summer in wet soils and lowest during winter months. ER had larger seasonal amplitude compared to GPP, and therefore drove the seasonal variation of NEE. Because summer carbon uptake may become increasingly limited by atmospheric demand and high temperature, and because ecosystem respiration could be enhanced by rising temperatures, our results suggest the potential for large-scale seasonal shifts in NEE in sclerophyll vegetation under climate change.

scholarly journals Dust Storms in Northern China: Long-Term Spatiotemporal Characteristics and Climate Controls

2017 ◽  
Vol 30 (17) ◽  
pp. 6683-6700 ◽  
Author(s):  
Qingyu Guan ◽  
Xiazhong Sun ◽  
Jing Yang ◽  
Baotian Pan ◽  
Shilei Zhao ◽  
...  
Keyword(s):  
Wind Speed ◽  
Dust Storm ◽  
Northern China ◽  
Dust Storms ◽  
Effect Of Temperature ◽  
Mean Annual Precipitation ◽  
Mean Annual Temperature ◽  
Spatiotemporal Characteristics ◽  
Dust Generation ◽  
The Mean

Airborne dust derived from desertification in northern China can be transported to East Asia and other regions, impairing human health and affecting the global climate. This study of northern China dust provides an understanding of the mechanism of dust generation and transportation. The authors used dust storm and climatological data from 129 sites and normalized difference vegetation index (NDVI) datasets in northern China to analyze spatiotemporal characteristics and determine the main factors controlling dust storms occurring during 1960–2007. Dust storm–prone areas are consistent with the spatial distribution of northern China deserts where the average wind speed (AWS) is more than 2 m s−1, the mean annual temperature (MAT) ranges from 5° to 10°C, and the mean annual precipitation (MAP) is less than 450 mm. Dust storms commonly occur on spring afternoons in a 3- to 6-h pattern. The three predominant factors that can affect DSF are the maximum wind speed, AWS, and MAT. During 1960–2007, dust storm frequency (DSF) in most regions of northern China fluctuated but had a decreasing trend; this was mainly caused by a gradual reduction in wind speed. The effect of temperature on DSF is complex, as positive and negative correlations exist simultaneously. Temperatures can affect source material (dust, sand, etc.), cyclone activity, and vegetation growth status, which influence the generation of dust storms. NDVI and precipitation are negatively correlated with DSF, but the effect is weak. Vegetation can protect the topsoil environment and prevent dust storm creation but is affected by the primary decisive influence of precipitation.

scholarly journals Rapid mass multiplication of Glomus mosseae inoculum as influenced by some biotic and abiotic factors

2018 ◽  
Vol 44 (2) ◽  
pp. 209-214 ◽  
Author(s):  
Subrata Nath Bhowmik ◽  
Gulab Singh Yadav ◽  
Mrinmay Datta
Keyword(s):  
Glomus Mosseae ◽  
Root Colonization ◽  
Abiotic Factors ◽  
Abiotic Factor ◽  
Biotic Factor ◽  
Biotic And Abiotic Factors ◽  
Chloris Gayana ◽  
Mycorrhizal Development ◽  
Chloris Gayana Kunth ◽  
Rapid Mass

Rhodes grasses (Chloris gayana Kunth) inoculated with Glomus mosseae were grown under the influence of Azospirillum (biotic factor), IAA (abiotic factor) and Hoagland’s solution (abiotic factor). The effectiveness of each factor was evaluated by measuring mycorrhizal root colonization and spore numbers. The pot culture experiment was carried out under polyhouse condition and observations were recorded at 45, 90 and 120 days of plant growth. The harvest date finely influenced the size of mycorrhizal inoculum. But, all biotic and abiotic factors had a greater influence on root colonization and spore multiplication than harvest time. The agents on application in conjunction favourably enhanced root infection and spore multiplication as compared to their solo treatments, with Azospirillum + Hoagland’s solution application posing to be the best. This not only stimulated mycorrhizal development, but also accelerated the root growth.

scholarly journals Biotic and abiotic factors distinctly drive contrasting biogeographic patterns between phyllosphere and soil resistomes in natural ecosystems

2021 ◽  
Vol 1 (1) ◽  
Author(s):  
Zhen-Zhen Yan ◽  
Qing-Lin Chen ◽  
Chao-Yu Li ◽  
Bao-Anh Thi Nguyen ◽  
Yong-Guan Zhu ◽  
...  
Keyword(s):  
Abiotic Factors ◽  
Antibiotic Resistance Genes ◽  
Terrestrial Ecosystems ◽  
Total Carbon ◽  
Mean Annual Temperature ◽  
Major Advance ◽  
Natural Ecosystems ◽  
Biotic Stresses ◽  
Biogeographic Patterns ◽  
Biotic And Abiotic Factors

AbstractThe phyllosphere and soil are two of the most important reservoirs of antibiotic resistance genes (ARGs) in terrestrial ecosystems. However, comparative studies on the biogeographic patterns of ARGs in these two habitats are lacking. Based on the construction of ARG abundance atlas across a > 4,000 km transect in eastern and northern Australia, we found contrasting biogeographic patterns of the phyllosphere and soil resistomes, which showed their distinct responses to the biotic and abiotic stresses. The similarity of ARG compositions in soil, but not in the phyllosphere, exhibited significant distance-decay patterns. ARG abundance in the phyllosphere was mainly correlated with the compositions of co-occurring bacterial, fungal and protistan communities, indicating that biotic stresses were the main drivers shaping the phyllosphere resistome. Soil ARG abundance was mainly associated with abiotic factors including mean annual temperature and precipitation as well as soil total carbon and nitrogen. Our findings demonstrated the distinct roles of biotic and abiotic factors in shaping resistomes in different environmental habitats. These findings constitute a major advance in our understanding of the current environmental resistomes and contribute to better predictions of the evolution of environmental ARGs by highlighting the importance of habitat difference in shaping environmental resistomes.

scholarly journals Assessing Terrestrial Ecosystem Resilience using Satellite Leaf Area Index

2020 ◽  
Vol 12 (4) ◽  
pp. 595
Author(s):  
Jinhui Wu ◽  
Shunlin Liang
Keyword(s):  
Positive Impact ◽  
Terrestrial Ecosystem ◽  
Remote Sensing Data ◽  
Terrestrial Ecosystems ◽  
Temporal Variations ◽  
Global Scale ◽  
Mean Annual Precipitation ◽  
Mean Annual Temperature ◽  
Ecosystem Resilience ◽  
Area Index

Quantitative approaches to measuring and assessing terrestrial ecosystem resilience, which expresses the ability of an ecosystem to recover from disturbances without shifting to an alternative state or losing function and services, is critical and essential to forecasting how terrestrial ecosystems will respond to global change. However, global and continuous terrestrial resilience measurement is fraught with difficulty, and the corresponding attribution of resilience dynamics is lacking in the literature. In this study, we assessed global terrestrial ecosystem resilience based on the long time-series GLASS LAI product and GIMMS AVHRR LAI 3g product, and validated the results using drought and fire events as the main disturbance indicators. We also analyzed the spatial and temporal variations of global terrestrial ecosystem resilience and attributed their dynamics to climate change and environmental factors. The results showed that arid and semiarid areas exhibited low resilience. We found that evergreen broadleaf forest exhibited the highest resilience (mean resilience value (from GLASS LAI): 0.6). On a global scale, the increase of mean annual precipitation had a positive impact on terrestrial resilience enhancement, while we found no consistent relationships between mean annual temperature and terrestrial resilience. For terrestrial resilience dynamics, we observed three dramatic raises of disturbance frequency in 1989, 1995, and 2001, respectively, along with three significant drops in resilience correspondingly. Our study mapped continuous spatiotemporal variation and captured interannual variations in terrestrial ecosystem resilience. This study demonstrates that remote sensing data are effective for monitoring terrestrial resilience for global ecosystem assessment.

scholarly journals Upside-down fluxes Down Under: CO<sub>2</sub> net sink in winter and net source in summer in a temperate evergreen broadleaf forest

2018 ◽  
Author(s):  
Alexandre A. Renchon ◽  
Anne Griebel ◽  
Christopher A. Williams ◽  
Belinda Medlyn ◽  
Remko A. Duursma ◽  
...  
Keyword(s):  
Large Scale ◽  
Ecosystem Respiration ◽  
Vapour Pressure Deficit ◽  
Summer Rainfall ◽  
Co2 Exchange ◽  
Mean Annual Precipitation ◽  
Surface Conductance ◽  
Mean Annual Temperature ◽  
Eddy Covariance Method ◽  
Area Index

Abstract. Predicting the seasonal dynamics of ecosystem carbon fluxes is challenging in broadleaved evergreen forests because of their moderate climates and subtle changes in canopy phenology. We assessed the climatic and biotic drivers of the seasonality of net ecosystem-atmosphere CO2 exchange (NEE) of a eucalyptus-dominated forest near Sydney, Australia, using the eddy covariance method. The climate is characterized by a mean annual precipitation of 800 mm and a mean annual temperature of 18 °C, hot summers and mild winters, with highly variable precipitation. In the three-year study, the ecosystem was a small sink in 2014 (54 g C m−2 y−1), a stronger sink in 2015 (183 g C m−2 y−1) and even stronger sink in 2016 (337 g C m−2 y−1), but these variations were not related to precipitation. Daily net C uptake was always detected during the cooler, drier winter months (June through August), while net C loss occurred during the warmer, wetter summer months (December through February). Gross primary productivity (GPP) seasonality was low, despite longer days with higher light intensity in summer, because vapour pressure deficit (D) and air temperature (Ta) restricted surface conductance during summer while winter temperatures were still high enough to support photosynthesis. Maximum GPP during ideal environmental conditions was correlated with canopy leaf area index (LAI) (r2 = 0.24), which increased rapidly after mid-summer rainfall events. Ecosystem respiration (ER) was highest during summer in wet soils and lowest during winter months. ER had larger seasonal amplitude compared to GPP, and therefore drove the seasonal variation of NEE. Because summer carbon uptake may become increasingly limited by atmospheric drought and high temperature, and ecosystem respiration could be enhanced by rising temperature, our results suggest the potential for large-scale seasonal shifts in NEE in sclerophyll vegetation under climate change.

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