Climate change and its impact on tea in Northeast India

2014 ◽  
Vol 5 (4) ◽  
pp. 625-632 ◽  
Author(s):  
Rishiraj Dutta
Keyword(s):  
Climate Change ◽  
Management Practices ◽  
Northeast India ◽  
Future Climate ◽  
Future Climate Change ◽  
Monthly Precipitation ◽  
Productivity Analysis ◽  
Climate Data ◽  
Tea Production ◽  
Production Period

The analysis of this study focused on the tea growing areas of Northeast India to provide predictions for future climate scenarios and its impact on tea production by 2050. The applied methodology involves a combination of current climate data with future climate change predictions from different models for 2050 as derived by WorldClim and IPCC4 (CIAT recommended). The results showed the possibility of an increase in average temperature by 2 °C in 2050, while not much variation is observed in the rainfall pattern. A change in tea production period is also expected by 2050 making tea planters look for alternative crops as an adaptive measure to keep the industry on its feet. With such expected impacts on tea production, the planters would need to make changes in their management practices to adapt to the evolving conditions and environment. In this study, the climate data were used as input to DIVA GIS Model. Monthly climate data were fed into Cranfield University Plantation Productivity Analysis for Tea Model (CUPPA Tea Model) to simulate observed and predicted yields. The study further shows that the overall climate will become less seasonal in terms of variation through the years followed by expected variations in monthly precipitation during the peak production months.

Projecting future vegetation change for northeast China using CMIP6

2020 ◽  
Author(s):  
Wei Yuan ◽  
Shuang-ye Wu ◽  
Shugui Hou
Keyword(s):  
Climate Change ◽  
Vegetation Change ◽  
Management Strategies ◽  
Future Climate ◽  
Future Climate Change ◽  
Vegetation Changes ◽  
Emission Scenarios ◽  
Climate Data ◽  
Climate Conditions ◽  
Temperature And Precipitation

<p>This study aims to establish future vegetation changes in the east and central of northern China (ECNC), an ecologically sensitive region in the transition zonal from humid monsoonal to arid continental climate. The region has experienced significant greening in the past several decades. However, few studies exist on how vegetation will change with future climate change, and great uncertainties exist due to complex, and often spatially non-stationary, relationships between vegetation and climate. In this study, we first used historical NDVI and climate data to model this spatially variable relationship with Geographically Weighted Logit Regression. We found that temperature and precipitation could explain, on average, 43% of NDVI variance, and they could be used to model NDVI fairly well. We then establish future climate change using the output of 11 CMIP6 models for the medium (SSP245) and high (SSP585) emission scenarios for the mid-century (2041-2070) and late-century (2071-2100). The results show that for this region, both temperature and precipitation will increase under both scenarios. By late-century under SSP585, precipitation is projected to increase by 25.12% and temperature is projected to increase 5.87<sup>o</sup>C in ECNC. Finally, we used future climate conditions as input for the regression models to project future vegetation (indicated by NDVI). We found that NDVI will increase under climate change. By mid-century, the average NDVI in ECNC will increase by 0.024 and 0.021 under SSP245 and SSP585. By late-century, it will increase by 0.016 and 0.006 under SSP245 and SSP585 respectively. Although NDVI is projected to increase, the magnitude of increase is likely to diminish with higher emission scenarios, possibly due to the benefit of precipitation increase being gradually encroached by the detrimental effects of temperature increase. Moreover, despite the overall NDVI increase, the area likely to suffer vegetation degradation will also expands, particularly in the western part of ECNC. With higher emissions and later into the century, region with low NDVI is likely to shift and/or expand north-forward. Our results could provide important information on possible vegetation changes, which could help to develop effective management strategies to ensure ecological and economic sustainability in the future.</p>

scholarly journals Impacts of future climate change on potential yields of major crops in China

2014 ◽  
Vol 5 (1) ◽  
pp. 617-647
Author(s):  
Y. Yin ◽  
Q. Tang ◽  
X. Liu
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Global Climate ◽  
Global Climate Models ◽  
Future Climate ◽  
Future Climate Change ◽  
Yield Reduction ◽  
Climate Data ◽  
Potential Yield ◽  
Crop Models

Abstract. Climate change may affect crop development and yield, and consequently cast a shadow of doubt over China's food self-sufficiency efforts. In this study we used the model projections of a couple of global gridded crop models (GGCMs) to assess the effects of future climate change on the potential yields of the major crops (i.e. wheat, rice, maize and soybean) over China. The GGCMs were forced with the bias-corrected climate data from 5 global climate models (GCMs) under the Representative Concentration Pathways (RCP) 8.5 which were made available by the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP). The results show that the potential yields of rice may increase over a large portion of China. Climate change may benefit food productions over the high-altitude and cold regions where are outside current main agricultural area. However, the potential yield of maize, soybean and wheat may decrease in a large portion of the current main crop planting areas such as North China Plain. Development of new agronomic management strategy may be useful for coping with climate change in the areas with high risk of yield reduction.

Projected climate change impacts on tropical life zones in Costa Rica

2021 ◽  
pp. 030913332110470
Author(s):  
Christian Birkel ◽  
Joni Dehaspe ◽  
Andrés Chavarría-Palma ◽  
Nelson Venegas-Cordero ◽  
Rene Capell ◽  
...  
Keyword(s):  
Climate Change ◽  
Costa Rica ◽  
Costa Rican ◽  
Future Climate ◽  
Future Climate Change ◽  
Climate Change Scenarios ◽  
Climate Data ◽  
Biological Corridors ◽  
Ecosystem Indicators ◽  
Near Future

Efforts to protect tropical ecosystems aim at implementing biological corridors across the national territory of Costa Rica. However, potential near-future climate change challenges the effectiveness of such conservation measures. For this purpose, we developed near-future climate change scenarios at high spatial resolution using open-access global data from the Copernicus Climate Data Store (CDS). These projections resulted from downscaling (to a 1km2 national grid) and quantile-mapping bias-correction of the Essential Climate Variables Global Circulation Model (ECV_GCM) ensemble mean from the CDS using a moderate Representative Concentration Pathway 4.5 (RCP4.5). Projections were evaluated with limited local station data and applied to generate future ecosystem indicators (Holdridge Life Zones, HLZs). We show significantly increasing temperatures of 2.6°C with a spatial variability of ± 0.4°C for Costa Rica until 2040 with local differences (higher temperatures projected for the southern Costa Rican Caribbean). The future mean annual precipitation showed slightly wetter conditions (120 ± 43 mm/year) and most prominently in the Costa Rican Caribbean and south Pacific, but no significant drying in the north of Costa Rica by 2040. The bias-corrected climate data were aggregated to decadal and 30-year average (1971–2040) life zone ecosystem indicators that could potentially show ecosystem shifts. Changes in the life zones are most likely due to warmer temperatures and to a lesser extent caused by projected wetter conditions. Shifts are more likely to occur at higher elevations with a potential loss of the sub-tropical rainforest ecosystem. The projections support diminishing tropical dry forests and slightly increasing tropical rain and wet forests in the biological corridors of the driest and wettest regions, respectively. A countrywide spatial uniformity of dominating tropical moist forests (increase from 24% to 49%) at the expense of other HLZs was projected by 2040.

BioDiv-Support: scenario-based decision support tool for policy planning and adaptation to future challenges in biodiversity and ecosystem services 

2021 ◽  
Author(s):  
Camilla Andersson ◽  
Keyword(s):  
Climate Change ◽  
Air Pollution ◽  
Ecosystem Services ◽  
Management Practices ◽  
Human Impacts ◽  
Future Climate ◽  
The Arctic ◽  
Future Climate Change ◽  
Local Stakeholders ◽  
The Impact

<p>Biodiversity includes any type of living variation, from the ecosystem level to genetic variation within organisms. The greatest threats to biodiversity is climate change, destruction of habitats and other human activities. High-altitude mountain regions are pristine environments, with historically small impacts from air pollution, but at risk of being disproportionately impacted by climate change. We focus on three mountainous regions: the Scandinavian Mountains, the Guadarrama Mountains in Spain, and the Pyrenees in France, Andorra and Spain. We study the impact of drivers of change of biodiversity such as future climate change, increased incidences of wild fires, emissions from new shipping routes in the Arctic as ice sheets are melting, human impacts on land use and management practices (such as reindeer grazing) and air pollution.</p><p>We simulate future climate change using WRF and a convective permitting climate model, HARMONIE-Climate, with a spatial resolution of 3km. The high resolution strongly improves the representation of precipitation compared to coarser scale simulations (Lind et al., 2020). We use these simulations to develop future scenarios of air pollution load, using two well established chemistry transport models (MATCH and CHIMERE; Marécal et al., 2015). These climate and air pollution scenarios are subsequently used, together with management scenarios, to develop scenarios for biodiversity and ecosystem services. These scenarios are developed applying a process-based dynamic vegetation and biogeochemistry model, LPJ-GUESS (Smith et al., 2014). </p><p>The scenarios, representing mid-21<sup>st</sup> century, will be made available through a web-based planning tool, where local stakeholders in each region can explore the project results to understand how scenarios of climate change, air pollution and policy development will affect these ecosystems. Local stakeholders are involved throughout the project, such as reindeer herder communities, regional county boards and national authorities, and in a time of changing climate and a global pandemic we have learned the necessity for flexibility in such interactions.</p><p> </p><p>References</p><p>Lind et al. 2020., Climate Dynamics 55, 1893-1912.</p><p>Marécal et al., 2015. Geosci. Mod. Dev. 8, 2777-2813.</p><p>Smith et al. 2014 Biogeosciences 11, 2027-2054.</p>

scholarly journals Phylogeography and niche modelling: reciprocal enlightenment

Mammalia ◽  
2019 ◽  
Vol 84 (1) ◽  
pp. 10-25 ◽  
Author(s):  
Govan Pahad ◽  
Claudine Montgelard ◽  
Bettine Jansen van Vuuren
Keyword(s):  
Climate Change ◽  
Genetic Diversity ◽  
Ecological Niche ◽  
Spatial Genetic Structure ◽  
Distribution Patterns ◽  
Future Climate ◽  
Future Climate Change ◽  
Environmental Niche ◽  
Climate Data ◽  
Niche Modelling

Abstract Phylogeography examines the spatial genetic structure of species. Environmental niche modelling (or ecological niche modelling; ENM) examines the environmental limits of a species’ ecological niche. These two fields have great potential to be used together. ENM can shed light on how phylogeographical patterns develop and help identify possible drivers of spatial structure that need to be further investigated. Specifically, ENM can be used to test for niche differentiation among clades, identify factors limiting individual clades and identify barriers and contact zones. It can also be used to test hypotheses regarding the effects of historical and future climate change on spatial genetic patterns by projecting niches using palaeoclimate or future climate data. Conversely, phylogeographical information can populate ENM with within-species genetic diversity. Where adaptive variation exists among clades within a species, modelling their niches separately can improve predictions of historical distribution patterns and future responses to climate change. Awareness of patterns of genetic diversity in niche modelling can also alert conservationists to the potential loss of genetically diverse areas in a species’ range. Here, we provide a simplistic overview of both fields, and focus on their potential for integration, encouraging researchers on both sides to take advantage of the opportunities available.

scholarly journals Warm climates of the past—a lesson for the future?

2013 ◽  
Vol 371 (2001) ◽  
pp. 20130146 ◽  
Author(s):  
D. J. Lunt ◽  
H. Elderfield ◽  
R. Pancost ◽  
A. Ridgwell ◽  
G. L. Foster ◽  
...  
Keyword(s):  
Climate Change ◽  
Numerical Models ◽  
Future Climate ◽  
Future Climate Change ◽  
Climate Data ◽  
Comprehensive Overview ◽  
Past Climate ◽  
The Past ◽  
The Future ◽  
Warm Climates

This Discussion Meeting Issue of the Philosophical Transactions A had its genesis in a Discussion Meeting of the Royal Society which took place on 10–11 October 2011. The Discussion Meeting, entitled ‘Warm climates of the past: a lesson for the future?’, brought together 16 eminent international speakers from the field of palaeoclimate, and was attended by over 280 scientists and members of the public. Many of the speakers have contributed to the papers compiled in this Discussion Meeting Issue. The papers summarize the talks at the meeting, and present further or related work. This Discussion Meeting Issue asks to what extent information gleaned from the study of past climates can aid our understanding of future climate change. Climate change is currently an issue at the forefront of environmental science, and also has important sociological and political implications. Most future predictions are carried out by complex numerical models; however, these models cannot be rigorously tested for scenarios outside of the modern, without making use of past climate data. Furthermore, past climate data can inform our understanding of how the Earth system operates, and can provide important contextual information related to environmental change. All past time periods can be useful in this context; here, we focus on past climates that were warmer than the modern climate, as these are likely to be the most similar to the future. This introductory paper is not meant as a comprehensive overview of all work in this field. Instead, it gives an introduction to the important issues therein, using the papers in this Discussion Meeting Issue, and other works from all the Discussion Meeting speakers, as exemplars of the various ways in which past climates can inform projections of future climate. Furthermore, we present new work that uses a palaeo constraint to quantitatively inform projections of future equilibrium ice sheet change.

scholarly journals Evidence of Climate Change Coping and Adaptation Practices by Smallholder Farmers in Northern Ghana

2021 ◽  
Vol 13 (3) ◽  
pp. 1308
Author(s):  
Philip Antwi-Agyei ◽  
Hanson Nyantakyi-Frimpong
Keyword(s):  
Climate Change ◽  
Management Practices ◽  
Smallholder Farmers ◽  
Future Climate ◽  
Northern Ghana ◽  
Future Climate Change ◽  
Climate Variations ◽  
Short Term ◽  
Adaptation Measures ◽  
Adaptation Practices

Evidence on how coping practices for immediate climate variations can transform into long-term adaptive capacity are relatively limited. This study addressed this gap by identifying the coping practices for short-term climate variations and the adaptation measures used by smallholder farmers to address future climate change in northeast Ghana. The paper used a mixed-methods approach, including household surveys, focus group discussions and key informant interviews. Data were collected from 555 households located in six communities across three districts in northeast Ghana. Results indicated that smallholder farmers were employing a host of practices to address the threats posed by climate change. Key adaptation practices included the planting of drought-tolerant crop varieties, the use of indigenous knowledge, intensification of irrigation, migration, adjusting the planting calendar, crop diversification, mixed farming, and sustainable land management practices. On the contrary, short-term coping practices reported by the study participants included the sale of non-farm assets, complementing agriculture with non-farm jobs, selling livestock, engaging in wage labor, charcoal burning and reliance on social networks. The results further revealed that barriers to climate change adaptation and coping practices differed by gender. The paper recommends that capacities of smallholder farmers in vulnerability hotspots should be enhanced to address immediate climate variations, as well as future climate changes. Ghana’s climate change and agricultural policies should prioritize adaptations by smallholder farmers in addressing threats posed by climate change.

scholarly journals Planning for Winter Road Maintenance in the Context of Climate Change

2017 ◽  
Vol 9 (3) ◽  
pp. 521-532 ◽  
Author(s):  
Lindsay Matthews ◽  
Jean Andrey ◽  
Ian Picketts
Keyword(s):  
Climate Change ◽  
Predictive Accuracy ◽  
Future Climate ◽  
Coefficient Of Determination ◽  
Future Climate Change ◽  
Road Maintenance ◽  
Climate Data ◽  
Winter Weather ◽  
Winter Road ◽  
Winter Road Maintenance

Abstract Winter weather creates mobility challenges for most northern jurisdictions, leading to significant expenditures on winter road maintenance (WRM) activities. While the science and practice of snow and ice control is continually evolving, climate change presents particular challenges for the strategic planning of WRM. The purpose of this study is 1) to develop a winter severity index (WSI) to better understand how winter weather translates into interannual variations in WRM activities and 2) to apply the WSI to future climate change projections to assist a northern community in preparing for climate change. A new method for creating a WSI model is explored, using readily available data from maintenance records and meteorological stations. The WSI is created by optimizing values for three levels of snowfall as well as potential icing events and is shown to have high predictive accuracy for WRM (coefficient of determination R2 of 0.93). The WSI is then applied to historic and future climate data in a municipality located in central British Columbia, Canada. Findings reveal that much of the variability in WRM can be attributed to weather. The results of the climate change analysis show that winter precipitation in the region is expected to increase by 5.2%–12.3%, and winter average temperatures are projected to increase by 1.5°–2.8°C in the 2050s, compared to the 1976–2000 baseline based on 65 GCMs. Based on the midrange (25th to 75th percentiles) of the 65 GCM projections, annual demand for WRM activities is estimated to decrease by 13.0%–22.0%.

Sign in / Sign up

Export Citation Format

Share Document