scholarly journals Vine vigor, yield and grape quality assessment by airborne remote sensing over three years: Analysis of unexpected relationships in cv. Tempranillo

2015 ◽  
Vol 13 (2) ◽  
pp. e0903 ◽  
Author(s):  
Irene Bonilla ◽  
Fernando Martinez de Toda ◽  
Jose Antonio Martínez-Casasnovas
Keyword(s):  
Climate Change ◽  
Remote Sensing ◽  
Spatial Variability ◽  
Vegetative Growth ◽  
Multispectral Imagery ◽  
Climate Conditions ◽  
Ripening Process ◽  
Stable Pattern ◽  
Grape Quality ◽  
High Spatial Variability

<p>The prediction of grape composition is becoming more important due to the need of reducing the current levels of alcohol and pH of the wines, a problem that is exacerbated by climate change. This work presents a 3-year study of the spatial variability of grape composition in a rainfed Tempranillo vineyard located in Rioja (Spain). It is based on the acquisition of multispectral imagery at <em>véraison</em> (start of the ripening process); and zoning based on NDVI, to assess its performance for zonal management. The results reveal a high spatial variability within the plot, with a stable pattern over the years, even with very different climate conditions. NDVI was a good predictor of vegetative growth variables. However, the prediction of grape composition was more complex. Unexpectedly, anthocyanins were found to be higher in the highest vigor zone, which is probably related to the effects of climate change. This unexpected relationship is particularly discussed in the article.</p>

scholarly journals PREDICTION OF CHANGES IN VEGETATION DISTRIBUTION UNDER CLIMATE CHANGE SCENARIOS USING MODIS DATASET

2016 ◽  
Vol XLI-B8 ◽  
pp. 883-887
Author(s):  
Hidetake Hirayama ◽  
Mizuki Tomita ◽  
Keitarou Hara
Keyword(s):  
Climate Change ◽  
Remote Sensing ◽  
Remote Sensing Data ◽  
Future Climate Change ◽  
Slope Aspect ◽  
Climate Change Scenarios ◽  
Vegetation Distribution ◽  
Climate Conditions ◽  
Distribution Maps ◽  
Sensing Data

The distribution of vegetation is expected to change under the influence of climate change. This study utilizes vegetation maps derived from Terra/MODIS data to generate a model of current climate conditions suitable to beech-dominated deciduous forests, which are the typical vegetation of Japan’s cool temperate zone. This model will then be coordinated with future climate change scenarios to predict the future distribution of beech forests. The model was developed by using the presence or absence of beech forest as the dependent variable. Four climatic variables; mean minimum daily temperature of the coldest month (TMC)，warmth index (WI)， winter precipitation (PRW) and summer precipitation (PRS): and five geophysical variables; topography (TOPO), surface geology (GEOL), soil (SOIL), slope aspect (ASP), and inclination (INCL); were adopted as independent variables. Previous vegetation distribution studies used point data derived from field surveys. The remote sensing data utilized in this study, however, should permit collecting of greater amounts of data, and also frequent updating of data and distribution maps. These results will hopefully show that use of remote sensing data can provide new insights into our understanding of how vegetation distribution will be influenced by climate change.

scholarly journals PREDICTION OF CHANGES IN VEGETATION DISTRIBUTION UNDER CLIMATE CHANGE SCENARIOS USING MODIS DATASET

2016 ◽  
Vol XLI-B8 ◽  
pp. 883-887
Author(s):  
Hidetake Hirayama ◽  
Mizuki Tomita ◽  
Keitarou Hara
Keyword(s):  
Climate Change ◽  
Remote Sensing ◽  
Remote Sensing Data ◽  
Future Climate Change ◽  
Slope Aspect ◽  
Climate Change Scenarios ◽  
Vegetation Distribution ◽  
Climate Conditions ◽  
Distribution Maps ◽  
Sensing Data

The distribution of vegetation is expected to change under the influence of climate change. This study utilizes vegetation maps derived from Terra/MODIS data to generate a model of current climate conditions suitable to beech-dominated deciduous forests, which are the typical vegetation of Japan’s cool temperate zone. This model will then be coordinated with future climate change scenarios to predict the future distribution of beech forests. The model was developed by using the presence or absence of beech forest as the dependent variable. Four climatic variables; mean minimum daily temperature of the coldest month (TMC)，warmth index (WI)， winter precipitation (PRW) and summer precipitation (PRS): and five geophysical variables; topography (TOPO), surface geology (GEOL), soil (SOIL), slope aspect (ASP), and inclination (INCL); were adopted as independent variables. Previous vegetation distribution studies used point data derived from field surveys. The remote sensing data utilized in this study, however, should permit collecting of greater amounts of data, and also frequent updating of data and distribution maps. These results will hopefully show that use of remote sensing data can provide new insights into our understanding of how vegetation distribution will be influenced by climate change.

Effect of Slope Mesorelief on the Spatial Variability of Soil Properties and Vegetation Index Based on Remote Sensing Data

2019 ◽  
Vol 55 (9) ◽  
pp. 1329-1337
Author(s):  
N. V. Gopp ◽  
T. V. Nechaeva ◽  
O. A. Savenkov ◽  
N. V. Smirnova ◽  
V. V. Smirnov
Keyword(s):  
Remote Sensing ◽  
Spatial Variability ◽  
Soil Properties ◽  
Vegetation Index ◽  
Remote Sensing Data ◽  
Sensing Data

scholarly journals Disentangling the Legacies of Climate and Management on Tree Growth

Ecosystems ◽  
2021 ◽  
Author(s):  
Laura Marqués ◽  
Drew M. P. Peltier ◽  
J. Julio Camarero ◽  
Miguel A. Zavala ◽  
Jaime Madrigal-González ◽  
...  
Keyword(s):  
Climate Change ◽  
Forest Management ◽  
Tree Growth ◽  
European Beech ◽  
Ring Formation ◽  
Silver Fir ◽  
Past Climate ◽  
Climate Conditions ◽  
Ecological Memory ◽  
Historical Forest

AbstractLegacies of past climate conditions and historical management govern forest productivity and tree growth. Understanding how these processes interact and the timescales over which they influence tree growth is critical to assess forest vulnerability to climate change. Yet, few studies address this issue, likely because integrated long-term records of both growth and forest management are uncommon. We applied the stochastic antecedent modelling (SAM) framework to annual tree-ring widths from mixed forests to recover the ecological memory of tree growth. We quantified the effects of antecedent temperature and precipitation up to 4 years preceding the year of ring formation and integrated management effects with records of harvesting intensity from historical forest management archives. The SAM approach uncovered important time periods most influential to growth, typically the warmer and drier months or seasons, but variation among species and sites emerged. Silver fir responded primarily to past climate conditions (25–50 months prior to the year of ring formation), while European beech and Scots pine responded mostly to climate conditions during the year of ring formation and the previous year, although these responses varied among sites. Past management and climate interacted in such a way that harvesting promoted growth in young silver fir under wet and warm conditions and in old European beech under drier and cooler conditions. Our study shows that the ecological memory associated with climate legacies and historical forest management is species-specific and context-dependent, suggesting that both aspects are needed to properly evaluate forest functioning under climate change.

scholarly journals Synergistic impacts of global warming and thermohaline circulation collapse on amphibians

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Julián A. Velasco ◽  
Francisco Estrada ◽  
Oscar Calderón-Bustamante ◽  
Didier Swingedouw ◽  
Carolina Ureta ◽  
...  
Keyword(s):  
Climate Change ◽  
Global Warming ◽  
Thermohaline Circulation ◽  
Climate Model ◽  
Global Climate ◽  
Extinction Risk ◽  
Meridional Overturning Circulation ◽  
Mitigation Strategies ◽  
Amphibian Species ◽  
Climate Conditions

AbstractImpacts on ecosystems and biodiversity are a prominent area of research in climate change. However, little is known about the effects of abrupt climate change and climate catastrophes on them. The probability of occurrence of such events is largely unknown but the associated risks could be large enough to influence global climate policy. Amphibians are indicators of ecosystems’ health and particularly sensitive to novel climate conditions. Using state-of-the-art climate model simulations, we present a global assessment of the effects of unabated global warming and a collapse of the Atlantic meridional overturning circulation (AMOC) on the distribution of 2509 amphibian species across six biogeographical realms and extinction risk categories. Global warming impacts are severe and strongly enhanced by additional and substantial AMOC weakening, showing tipping point behavior for many amphibian species. Further declines in climatically suitable areas are projected across multiple clades, and biogeographical regions. Species loss in regional assemblages is extensive across regions, with Neotropical, Nearctic and Palearctic regions being most affected. Results underline the need to expand existing knowledge about the consequences of climate catastrophes on human and natural systems to properly assess the risks of unabated warming and the benefits of active mitigation strategies.

scholarly journals Analysing the Impact of Climate Change on Hydrological Ecosystem Services in Laguna del Sauce (Uruguay) Using the SWAT Model and Remote Sensing Data

2021 ◽  
Vol 13 (10) ◽  
pp. 2014
Author(s):  
Celina Aznarez ◽  
Patricia Jimeno-Sáez ◽  
Adrián López-Ballesteros ◽  
Juan Pablo Pacheco ◽  
Javier Senent-Aparicio
Keyword(s):  
Climate Change ◽  
Remote Sensing ◽  
Ecosystem Services ◽  
Water Resources ◽  
Swat Model ◽  
Remote Sensing Data ◽  
Erosion Control ◽  
Sensing Data ◽  
Extreme Precipitation Events ◽  
The Impact

Assessing how climate change will affect hydrological ecosystem services (HES) provision is necessary for long-term planning and requires local comprehensive climate information. In this study, we used SWAT to evaluate the impacts on four HES, natural hazard protection, erosion control regulation and water supply and flow regulation for the Laguna del Sauce catchment in Uruguay. We used downscaled CMIP-5 global climate models for Representative Concentration Pathways (RCP) 2.6, 4.5 and 8.5 projections. We calibrated and validated our SWAT model for the periods 2005–2009 and 2010–2013 based on remote sensed ET data. Monthly NSE and R2 values for calibration and validation were 0.74, 0.64 and 0.79, 0.84, respectively. Our results suggest that climate change will likely negatively affect the water resources of the Laguna del Sauce catchment, especially in the RCP 8.5 scenario. In all RCP scenarios, the catchment is likely to experience a wetting trend, higher temperatures, seasonality shifts and an increase in extreme precipitation events, particularly in frequency and magnitude. This will likely affect water quality provision through runoff and sediment yield inputs, reducing the erosion control HES and likely aggravating eutrophication. Although the amount of water will increase, changes to the hydrological cycle might jeopardize the stability of freshwater supplies and HES on which many people in the south-eastern region of Uruguay depend. Despite streamflow monitoring capacities need to be enhanced to reduce the uncertainty of model results, our findings provide valuable insights for water resources planning in the study area. Hence, water management and monitoring capacities need to be enhanced to reduce the potential negative climate change impacts on HES. The methodological approach presented here, based on satellite ET data can be replicated and adapted to any other place in the world since we employed open-access software and remote sensing data for all the phases of hydrological modelling and HES provision assessment.

scholarly journals The Exploitation of Local Vitis vinifera L. Biodiversity as a Valuable Tool to Cope with Climate Change Maintaining Berry Quality

Plants ◽  
2020 ◽  
Vol 10 (1) ◽  
pp. 71
Author(s):  
María Carmen Antolín ◽  
María Toledo ◽  
Inmaculada Pascual ◽  
Juan José Irigoyen ◽  
Nieves Goicoechea
Keyword(s):  
Climate Change ◽  
Fruit Quality ◽  
Atmospheric Carbon Dioxide ◽  
Antioxidant Properties ◽  
Co2 Concentration ◽  
Soluble Solids ◽  
Vitis Vinifera L ◽  
Grape Quality ◽  
Berry Quality ◽  
Carbon Dioxide Co2

(1) Background: The associated increase in global mean surface temperature together with raised atmospheric carbon dioxide (CO2) concentration is exerting a profound influence on grapevine development (phenology) and grape quality. The exploitation of the local genetic diversity based on the recovery of ancient varieties has been proposed as an interesting option to cope with climate change and maintaining grape quality. Therefore, this research aimed to characterize the potential fruit quality of genotypes from seven local old grapevine varieties grown under climate change conditions. (2) Methods: The study was carried out on fruit-bearing cuttings (one cluster per plant) that were grown in pots in temperature gradient greenhouses (TGG). Two treatments were applied from fruit set to maturity: (1) ambient CO2 (400 ppm) and temperature (T) (ACAT) and (2) elevated CO2 (700 ppm) and temperature (T + 4 °C) (ECET). (3) Results: Results showed that some of the old genotypes tested remained quite stable during the climate change conditions in terms of fruit quality (mainly, total soluble solids and phenolic content) and of must antioxidant properties. (4) Conclusion: This research underlines the usefulness of exploiting local grapevine diversity to cope with climate change successfully, although further studies under field conditions and with whole plants are needed before extrapolating the results to the vineyard.

scholarly journals Multispectral Remote Sensing of Wetlands in Semi-Arid and Arid Areas: A Review on Applications, Challenges and Possible Future Research Directions

2020 ◽  
Vol 12 (24) ◽  
pp. 4190
Author(s):  
Siyamthanda Gxokwe ◽  
Timothy Dube ◽  
Dominic Mazvimavi
Keyword(s):  
Remote Sensing ◽  
Arid Regions ◽  
Remote Sensing Data ◽  
Sub Saharan Africa ◽  
Future Research ◽  
Multispectral Imagery ◽  
Aquatic Life ◽  
Sensing Data ◽  
Spatial Coverage ◽  
Semi Arid

Wetlands are ranked as very diverse ecosystems, covering about 4–6% of the global land surface. They occupy the transition zones between aquatic and terrestrial environments, and share characteristics of both zones. Wetlands play critical roles in the hydrological cycle, sustaining livelihoods and aquatic life, and biodiversity. Poor management of wetlands results in the loss of critical ecosystems goods and services. Globally, wetlands are degrading at a fast rate due to global environmental change and anthropogenic activities. This requires holistic monitoring, assessment, and management of wetlands to prevent further degradation and losses. Remote-sensing data offer an opportunity to assess changes in the status of wetlands including their spatial coverage. So far, a number of studies have been conducted using remotely sensed data to assess and monitor wetland status in semi-arid and arid regions. A literature search shows a significant increase in the number of papers published during the 2000–2020 period, with most of these studies being in semi-arid regions in Australia and China, and few in the sub-Saharan Africa. This paper reviews progress made in the use of remote sensing in detecting and monitoring of the semi-arid and arid wetlands, and focuses particularly on new insights in detection and monitoring of wetlands using freely available multispectral sensors. The paper firstly describes important characteristics of wetlands in semi-arid and arid regions that require monitoring in order to improve their management. Secondly, the use of freely available multispectral imagery for compiling wetland inventories is reviewed. Thirdly, the challenges of using freely available multispectral imagery in mapping and monitoring wetlands dynamics like inundation, vegetation cover and extent, are examined. Lastly, algorithms for image classification as well as challenges associated with their uses and possible future research are summarised. However, there are concerns regarding whether the spatial and temporal resolutions of some of the remote-sensing data enable accurate monitoring of wetlands of varying sizes. Furthermore, it was noted that there were challenges associated with the both spatial and spectral resolutions of data used when mapping and monitoring wetlands. However, advancements in remote-sensing and data analytics provides new opportunities for further research on wetland monitoring and assessment across various scales.

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