Rootstock effect on tree-ring traits in grapevine under a climate change scenario

IAWA Journal ◽  
2018 ◽  
Vol 39 (2) ◽  
pp. 145-155 ◽  
Author(s):  
Veronica De Micco ◽  
Enrica Zalloni ◽  
Giovanna Battipaglia ◽  
Arturo Erbaggio ◽  
Pasquale Scognamiglio ◽  
...  
Keyword(s):  
Tree Ring ◽  
Wood Anatomy ◽  
Climate Change Scenario ◽  
Southern Italy ◽  
Change Scenario ◽  
Volcanic Area ◽  
Plant Cultivation ◽  
Wood Traits ◽  
Projected Changes ◽  
Drought Occurrence

ABSTRACTProjected changes in drought occurrence in the Mediterranean region are raising concerns about the adaptive capability of rainfed crops, such as grapevine, to increasing aridity. Cultivation management, especially the techniques influencing the hydraulic pathway, can play a role in plant adaptation to drought for the consequent changes in wood anatomical functional traits. The aim of this study was to assess the effect of grafting on wood anatomy in tree-ring series ofVitis vini-feraL. ‘Piedirosso’ grapevine cultivated in a volcanic area in Southern Italy. Tree-ring anatomy was analysed in vines grown on their own roots or grafted onto 420A rootstock. Results showed that grafted vines had a higher occurrence of wood traits linked with safety of water transport if compared with non-grafted vines. Grafting induced the formation of tree rings with higher incidence of latewood also characterised by narrower and more frequent vessels if compared with non-grafted vines. This study suggested a different regulation of water flow in the grafted and non-grafted vines. Such findings support the analysis of wood anatomy as a tool to drive decisions linked with plant cultivation management. In this specific case, our results encourage to further explore the change from a traditional cultivation with own-rooted grapevines towards grafted models inducing better xylem adaptation to increasing drought.

scholarly journals Uncertainty of Streamflow Forecasting with the Climate Change Scenario in India

2020 ◽  
Vol 1 (3) ◽  
Author(s):  
Ankit Bhatt ◽  
Ajay Pradhan
Keyword(s):  
Climate Change ◽  
Large Scale ◽  
Climate Change Scenario ◽  
Climate Models ◽  
Spatial Scales ◽  
Global Climate Models ◽  
Seasonal Effects ◽  
Change Scenario ◽  
Streamflow Forecasting ◽  
Projected Changes

Streamflow and rainfall estimates have utmost importance to compute detailed water availability and hydrology for many sectors such as agriculture, water management, and food security. There are various models developed over the years for runoff estimation but among them only a few models incorporate climate change factors. Snowmelt and rainfall are the main sources of surface as well as groundwater resource and the main inputs in runoff models for estimation of streamflow. There are numerous factors which leads to climate change which intern affects the distribution on rainfall on spatial and temporal scales and the rate of melting of snows in the Himalayan region. Uncertainties in projected changes in the hydrological systems arise from internal variability in the climatic system, uncertainty about future greenhouse gas and aerosol emissions, the translations of these emissions into climate change by global climate models, and hydrological model uncertainty. Projections become less consistent between models as the spatial scale decreases. The uncertainty of climate model projections for freshwater assessments is often taken into account by using multi-model ensembles. The multi-model ensemble approach is, however, not a guarantee of reducing uncertainty in mathematical models. In recent years the floods have occurred due to high intensity rainfall occurred in a very short time, but in several cases the flooding has also occurred because the rainfall has fallen at times when all the storage systems have not been emptied after the previous rainfall. This is what we call coupled rainfall. There is currently no recommendation for how to take coupled rainfall account when applying the climate change scenario. It is estimated that such changes represent at a large scale, and cannot be applied to shorter temporal and smaller spatial scales. In areas where rainfall and runoff are very low (e.g., desert areas), small changes in runoff can lead to large percentage changes. In some regions, the sign of projected changes in runoff differs from recently observed trends. Moreover, in some areas with projected increases in runoff, different seasonal effects are expected, such as increased wet season runoff and decreased dry season runoff. Studies using results from fewer climate models can be considerably different from the other models

Possible vegetation change in Mountain Altai under climate warming and compiling the prognosis maps

2000 ◽  
pp. 26-31
Author(s):  
E. I. Parfenova ◽  
N. M. Chebakova
Keyword(s):  
Climate Warming ◽  
Vegetation Change ◽  
Climate Change Scenario ◽  
Change Scenario ◽  
Forest Steppe ◽  
Vegetation Map ◽  
Climatic Indices ◽  
Bioclimatic Model ◽  
Open Woodland ◽  
Mountain Taiga

Global climate warming is expected to be a new factor influencing vegetation redistribution and productivity in the XXI century. In this paper possible vegetation change in Mountain Altai under global warming is evaluated. The attention is focused on forest vegetation being one of the most important natural resources for the regional economy. A bioclimatic model of correlation between vegetation and climate is used to predict vegetation change (Parfenova, Tchebakova 1998). In the model, a vegetation class — an altitudinal vegetation belt (mountain tundra, dark- coniferous subalpine open woodland, light-coniferous subgolets open woodland, dark-coniferous mountain taiga, light-coniferous mountain taiga, chern taiga, subtaiga and forest-steppe, mountain steppe) is predicted from a combination of July Temperature (JT) and Complex Moisture Index (CMI). Borders between vegetation classes are determined by certain values of these two climatic indices. Some bioclimatic regularities of vegetation distribution in Mountain Altai have been found: 1. Tundra is separated from taiga by the JT value of 8.5°C; 2. Dark- coniferous taiga is separated from light-coniferous taiga by the CMI value of 2.25; 3. Mountain steppe is separated from the forests by the CMI value of 4.0. 4. Within both dark-coniferous and light-coniferous taiga, vegetation classes are separated by the temperature factor. For the spatially model of vegetation distribution in Mountain Altai within the window 84 E — 90 E and 48 N — 52 N, the DEM (Digital Elevation Model) was used with a pixel of 1 km resolution. In a GIS Package IDRISI for Windows 2.0, climatic layers were developed based on DEM and multiple regressions relating climatic indices to physiography (elevation and latitude). Coupling the map of climatic indices with the authors' bioclimatic model resulted into a vegetation map for the region of interest. Visual comparison of the modelled vegetation map with the observed geobotanical map (Kuminova, 1960; Ogureeva, 1980) showed a good similarity between them. The new climatic indices map was developed under the climate change scenario with summer temperature increase 2°C and annual precipitation increase 20% (Menzhulin, 1998). For most mountains under such climate change scenario vegetation belts would rise 300—400 m on average. Under current climate, the dark-coniferous and light-coniferous mountain taiga forests dominate throughout Mountain Altai. The chern forests are the most productive and floristically rich and are also widely distributed. Under climate warming, light-coniferous mountain taiga may be expected to transform into subtaiga and forest-steppe and dark-coniferous taiga may be expected to transform partly into chern taiga. Other consequences of warming may happen such as the increase of forest productivity within the territories with sufficient rainfall and the increase of forest fire occurrence over territories with insufficient rainfall.

scholarly journals Simulating Agroforestry Adoption in Rural Indonesia: The Potential of Trees on Farms for Livelihoods and Environment

Land ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 385
Author(s):  
Beatrice Nöldeke ◽  
Etti Winter ◽  
Yves Laumonier ◽  
Trifosa Simamora
Keyword(s):  
Climate Change ◽  
Climate Change Scenario ◽  
Agroforestry System ◽  
Environmental Benefits ◽  
Small Scale ◽  
Change Scenario ◽  
Trees On Farms ◽  
Agroforestry Adoption ◽  
Mitigate Climate Change ◽  
Small Scale Farmers

In recent years, agroforestry has gained increasing attention as an option to simultaneously alleviate poverty, provide ecological benefits, and mitigate climate change. The present study simulates small-scale farmers’ agroforestry adoption decisions to investigate the consequences for livelihoods and the environment over time. To explore the interdependencies between agroforestry adoption, livelihoods, and the environment, an agent-based model adjusted to a case study area in rural Indonesia was implemented. Thereby, the model compares different scenarios, including a climate change scenario. The agroforestry system under investigation consists of an illipe (Shorea stenoptera) rubber (Hevea brasiliensis) mix, which are both locally valued tree species. The simulations reveal that farmers who adopt agroforestry diversify their livelihood portfolio while increasing income. Additionally, the model predicts environmental benefits: enhanced biodiversity and higher carbon sequestration in the landscape. The benefits of agroforestry for livelihoods and nature gain particular importance in the climate change scenario. The results therefore provide policy-makers and practitioners with insights into the dynamic economic and environmental advantages of promoting agroforestry.

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