Indicators of climate change in agricultural systems

Hatfield, Jerry L.; Antle, John M.; Garrett, Karen A.; Izaurralde, R. C.; Mader, Terry L.; Marshall, Elizabeth; Nearing, M. A.; Robertson, G. Philip; Ziska, Lewis

doi:10.1007/s10584-018-2222-2

Cited by 115 publications

(61 citation statements)

References 37 publications

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“…Although data on the effects of climate change and particularly on glacial melting is conflicting, it is evident that changes in precipitation and temperature increases are leading to increased vulnerability in the region. Climate change is affecting the seasonality of rainfall, which affects agricultural productivity, health, water and food and security [56][57][58]. While comparing the vulnerability ratio with the data published by MoE, 2010, the sensitivity index of all study areas is increasing.…”

Section: Discussionmentioning

confidence: 96%

Climate Change Vulnerability Assessment in the High Mountain Region of Nepal: A Case Study of Lamjung District

Rai

Neupane

Pariyar

2020

IJECC

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Climate change vulnerability has need access to targeted scientiﬁc information about the impacts of climate change in order to adapt to its effects. Awareness can be measured through three different parameters-conceptualization, engagement and experimental. This research has conduct in Lamjung district where people are victimize from climate change. Primary and secondary sources of data are used. This study used household surveys and focus group discussions to assess people perceptions of these changes and identify the climate change vulnerability. Thus, the present study aimed to evaluate the Lamjung districts, vulnerable in the context of the climate change. This result is useful for policymaker, local government and different stockholder who are working on climate change sector. It is also important for long term changes in climate variables and occurrences of natural disasters is the most important component to determine the overall vulnerability. Climate change vulnerability had been decreased considerably in this study area. Meanwhile, long-term research in Nepal is required for extensive work on climate change and primary data collection for climate change vulnerability assessment.

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Section: Discussionmentioning

confidence: 96%

Climate Change Vulnerability Assessment in the High Mountain Region of Nepal: A Case Study of Lamjung District

Rai

Neupane

Pariyar

2020

IJECC

View full text Add to dashboard Cite

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“…These indicators are an average area of holdings (hectares), average livestock units of holdings (livestock units), an average labor force of holdings (annual work units) and average standard output of holdings (euros). The key indicators for the composite indicator of climatic features, including temperature (centigrade) and rainfall (millimeter) [33], are available on the World Bank website. Lastly, the indicators of economic conditions are gross domestic product per capita (dollars) and an index of domestic food price levels [32].…”

Section: Datamentioning

confidence: 99%

New Evaluation of Small Farms: Implication for an Analysis of Food Security

2020

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Farm structure is a multi-dimensional concept that can be measured through different criteria. Meanwhile, farm structure has been identified to discern small farms or well-endowed farms from the other farms. Distinguishing and identifying these two groups have practical implications for understanding the dynamics in rural areas and the effectiveness of target measures in these categories. The existing literature lacks a better definition of small farms based on the different criteria used. In this paper, we have developed composite indicators to apply to the concept of farm structure to re-define small farms and discover their role in achieving food security in Europe. By clustering countries using the composite indicator of farm structure, we estimate that more than 80 percent of food across Europe is produced by multi-criteria small and medium farms, but the partial productivities of agricultural land and labor in these countries that have the majority of multi-criteria small and medium farms are much lower than the large ones. Then, an estimate of a spatial econometric regression model was done to recognize how farm structure, a representative of farm size, can affect food availability, which is representative of food security. The results show that improving the structure of farms in a country not only improves its food security but also improves its neighbors’ food security. Hence, improving the structure of multi-criteria small farms is a major part of the solution to improve and achieve food security. Recognizing and understanding the diversity of multi-criteria small farms by considering the specific products and countries is necessary for designing appropriate innovations and policies for supporting more productive multi-criteria small farms.

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“…The exceedance area above the threshold X is defined analogously to the degree days (Gosling et al 2013) but with the selected parameter x i being used on an hourly basis instead of daily mean values, with the results in Kh a −1 for the air temperature (temperature difference is given Maximum volume flow rate, V max , by maximum temperature difference between indoor and outdoor of 3 K and a body mass m = 120 kg in K (Kelvin)) and h a −1 for the THI (because THI is dimensionless). All parameters describing heat stress in pigs were calculated as annual sums over the 37-year period (1981-2017), as suggested by Hatfield et al (2018).…”

Section: Heat Stress Parameters For Growing-fattening Pigsmentioning

confidence: 99%