Agronomic impacts of climate variability on rice production in the Philippines

Lansigan, Felino P.; Santos, W. L. de los; Coladilla, Jesusita O.

doi:10.1016/s0167-8809(00)00222-x

Cited by 115 publications

(73 citation statements)

References 11 publications

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“…Moreover, climate change triggers increased temperatures, changing rainfall, patterns and amounts, and a higher frequency and intensity of extreme climate events such as floods, cyclone, droughts and heat wave [17] [18]. However, temperature increases and erratic rainfall patterns affect crop agriculture mostly directly cum adversely [19] [20] [21], and by extension, food I. N. Nwachukwu, C. A. Shisanya 4/10 OALib Journal security. Changes in climate generally involve changes in two major climate variables: temperature and precipitation.…”

Section: Methodsmentioning

confidence: 99%

Determinants of Agricultural Production in Kenya under Climate Change

Nwachukwu¹,

Shisanya²

2017

OALib

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Climate change has been described as the most significant environmental threat of the 21 st century with vast impact mostly on agriculture, altering food production processes. As an important sector in the Kenyan economy, agriculture continues to dominate other sectors despite its declining contribution to real GDP. Given that the performance of the agricultural sector is determined by a large number of factors, the need to articulate this study has become imperative in view of the climate phenomenon. Therefore, the study examined the determinants of agricultural production in Kenya under climate change with specific interests in assessing the trend of climate variables and growth rate of agricultural production within 1970-2012 periods; estimating factors influencing agricultural production and deducing policy implications from the findings. Data used were secondary and include value of agricultural production, livestock, machines, fertilizer, agricultural land, labour, annual precipitation and temperature over the study period. These were obtained from databases hosted by the Food and Agriculture Organization (FAOSTAT), the World Bank and United Nations Development Programme (UNDP). Data analysis was done using trend analysis, log quadratic trend equation and multiple regression model. The trend results show that precipitation pattern traced out high amplitude decadal variability with the forecast showing off a slightly upward trend. In temperature, the inter-annual variability observed was wide with a forecast of a slight increase up to 2020. In terms of growth analysis, the log quadratic equation indicates that agricultural production posted a compound growth rate of 3.252% during the period while production was determined by the quantum of labour, livestock, agricultural land, precipitation and its squared term. The implication is that precipitation both on the short and long run affected agricultural production. It is recommended that ecosystem based and technologically driven adaptation measures be taken to address climate change effects on agricultural production.

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Section: Methodsmentioning

confidence: 99%

Determinants of Agricultural Production in Kenya under Climate Change

Nwachukwu¹,

Shisanya²

2017

OALib

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“…All rice, whether rain-fed or irrigated, is sensitive to a number of climate variables including precipitation, vapor pressure, soil moisture, seasonal temperature, daily maximum and minimum temperatures, solar radiation and annual input of atmospheric carbon dioxide (CO 2 ) concentration (Lansigan et al 2000;Wassmann et al 2009). Both long-term changes in climate and its variability (e.g.…”

Section: Agricultural Production Ricementioning

confidence: 99%

“…drought) influence rice productivity and yield. The effects of short-term events and extremes on yield largely depend on the development stage of the crop at the time of exposure, with dry rice being generally more sensitive than irrigated rice (Lansigan et al 2000). …”

Section: Agricultural Production Ricementioning

confidence: 99%

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Integrating adaptation into REDD+: potential impacts and social return on investment in Setulang, Malinau District, Indonesia

Pramova¹,

Locatelli²,

Mench³

et al. 2013

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“…Hence, in this empirical study, we only analyze rice loss caused by typhoons. Related rice losses caused by typhoons in Japan (Yamagata et al, 1988;Yamamoto et al, 2000;Ji et al, 2002;Yamamoto and Iwaya, 2006) and the Philippines (Lansigan et al, 2000) have also been investigated. Luo et al (1998) attempted to apply the concept of risk assessment to estimate the probability of certain levels of rice-yield loss for five Asian countries.…”

Section: Introductionmentioning

confidence: 99%

Risk Analysis of Rice Losses Caused by Typhoon for Taiwan

Lai

2010

CMR

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This paper applies extreme value theory to the Taiwanese rice loss caused by typhoons to demonstrate how these new statistical tools can be used to improve quantitative risk management. The application of the extreme value theory to statistics allowed us to test models with data from the upper tail of a distribution. Using the block-max and peak-over-threshold approaches to extreme value modeling, we matched generalized extreme value distribution (GEVD) and generalized Pareto distribution (GPD) to agricultural losses caused by natural disasters, with Taiwanese data from 1971 to 2005. We then evaluated the appropriateness of the upper tail fitting to loss data by comparing with standard parametric modeling that is based on lognormal and gamma distributions. The extreme value theory outperforms classical parametric fits for the largest observed historical losses. Finally, we draw particular attention to issues related to agricultural disaster and calculate the 90th, 95th, and 99th percentile of VaR and expected shortfall. These results could help the authorities or agriculture risk managers to check the applicable loss-compensation regulations.

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Agronomic impacts of climate variability on rice production in the Philippines

Cited by 115 publications

References 11 publications

Determinants of Agricultural Production in Kenya under Climate Change

Determinants of Agricultural Production in Kenya under Climate Change

Integrating adaptation into REDD+: potential impacts and social return on investment in Setulang, Malinau District, Indonesia

Risk Analysis of Rice Losses Caused by Typhoon for Taiwan

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