scholarly journals Managing fire risk during drought: the influence of certification and El Niño on fire-driven forest conversion for oil palm in Southeast Asia

2017 ◽  
Vol 8 (3) ◽  
pp. 749-771 ◽  
Author(s):  
Praveen Noojipady ◽  
Douglas C. Morton ◽  
Wilfrid Schroeder ◽  
Kimberly M. Carlson ◽  
Chengquan Huang ◽  
...  

Abstract. Indonesia and Malaysia have emerged as leading producers of palm oil in the past several decades, expanding production through the conversion of tropical forests to industrial plantations. Efforts to produce sustainable palm oil, including certification by the Roundtable on Sustainable Palm Oil (RSPO), include guidelines designed to reduce the environmental impact of palm oil production. Fire-driven deforestation is prohibited by law in both countries and a stipulation of RSPO certification, yet the degree of environmental compliance is unclear, especially during El Niño events when drought conditions increase fire risk. Here, we used time series of satellite data to estimate the spatial and temporal patterns of fire-driven deforestation on and around oil palm plantations. In Indonesia, fire-driven deforestation accounted for one-quarter of total forest losses on both certified and noncertified plantations. After the first plantations in Indonesia received RSPO certification in 2009, forest loss and fire-driven deforestation declined on certified plantations but did not stop altogether. Oil palm expansion in Malaysia rarely involved fire; only 5 % of forest loss on certified plantations had coincident active fire detections. Interannual variability in fire detections was strongly influenced by El Niño and the timing of certification. Fire activity during the 2002, 2004, and 2006 El Niño events was similar among oil palm plantations in Indonesia that would later become certified, noncertified plantations, and surrounding areas. However, total fire activity was 75 % and 66 % lower on certified plantations than noncertified plantations during the 2009 and 2015 El Niño events, respectively. The decline in fire activity on certified plantations, including during drought periods, highlights the potential for RSPO certification to safeguard carbon stocks in peatlands and remaining forests in accordance with legislation banning fires. However, aligning certification standards with satellite monitoring capabilities will be critical to realize sustainable palm oil production and meet industry commitments to zero deforestation.

2017 ◽  
Author(s):  
Praveen Noojipady ◽  
Douglas C. Morton ◽  
Wilfrid Schroeder ◽  
Kimberly M. Carlson ◽  
Chengquan Huang ◽  
...  

Abstract. Indonesia and Malaysia have emerged as leading producers of palm oil in the past several decades, expanding production through the conversion of tropical forests to industrial plantations. Efforts to produce "sustainable" palm oil, including certification by the Roundtable on Sustainable Palm Oil (RSPO), include guidelines designed to reduce the environmental impact of palm oil production. Fire-driven deforestation is prohibited by law in both countries and a stipulation of RSPO certification, yet the degree of environmental compliance is unclear, especially during El Niño events when drought conditions increase fire risk. Here, we used time series of satellite data to estimate the spatial and temporal patterns of fire-driven deforestation in and around oil palm plantations. In Indonesia, fire-driven deforestation accounted for one quarter of total forest losses in both certified and non-certified plantations. After the first plantations in Indonesia received RSPO certification in 2009, forest loss and fire-driven deforestation declined in certified plantations but did stop altogether. Oil palm expansion in Malaysia rarely involved fire; only 6 % of forest loss in certified plantations had coincident active fire detections. Interannual variability in fire detections was strongly influenced by El Niño and the timing of certification. Fire activity during the 2002, 2004, and 2006 El Niño event was similar among oil palm plantations in Indonesia that would later become certified, non-certified plantations, and surrounding areas. However, rates of fire activity were 57 % and 44 % lower in certified plantations than non-certified plantations during the 2009 and 2015 El Niño events, respectively. The decline in fire activity on certified plantations, including during drought periods, highlights the potential for RSPO certification to safeguard carbon stocks in peatlands and remaining forests and support legislation banning fires. However, aligning certification standards with satellite monitoring capabilities will be critical to realize sustainable palm oil production and meet industry commitments to zero deforestation.


Agronomy ◽  
2021 ◽  
Vol 11 (11) ◽  
pp. 2189
Author(s):  
Jen Feng Khor ◽  
Lloyd Ling ◽  
Zulkifli Yusop ◽  
Wei Lun Tan ◽  
Joan Lucille Ling ◽  
...  

Oil palm crop yield is sensitive to heat and drought. Therefore, El Niño events affect oil palm production, resulting in price fluctuations of crude palm oil due to global supply shortage. This study developed a new Fresh Fruit Bunch Index (FFBI) model based on the monthly oil palm fresh fruit bunch (FFB) yield data, which correlates directly with the Oceanic Niño Index (ONI) to model the impact of past El Niño events in Malaysia in terms of production and economic losses. FFBI is derived from Malaysian monthly FFB yields from January 1986 to July 2021 in the same way ONI is derived from monthly sea surface temperatures (SST). With FFBI model, the Malaysian oil palm yields are better correlated with ONI and have higher predictive ability. The descriptive and inferential statistical assessments show that the newly proposed FFBI time series model (adjusted R-squared = 0.9312 and residual median = 0.0051) has a better monthly oil palm yield predictive ability than the FFB model (adjusted R-squared = 0.8274 and residual median = 0.0077). The FFBI model also revealed an oil palm under yield concern of the Malaysian oil palm industry in the next thirty-month forecasted period from July 2021 to December 2023.


2004 ◽  
Vol 13 (2) ◽  
pp. 165 ◽  
Author(s):  
Danielle C. Verdon ◽  
Anthony S. Kiem ◽  
Stewart W. Franks

This study investigates the influence that the El Niño/Southern Oscillation (ENSO) and the Inter-decadal Pacific Oscillation (IPO) have on long term daily weather conditions pertinent to high forest fire danger in New South Wales, Australia. Using historical meteorological data for 22 weather stations to compute the daily value of McArthur’s Forest Fire Danger Index (FFDI), it is shown that a strong relationship exists between climate variability, on a range of time scales, and forest fire risk. An investigation into the influence of ENSO on fire risk demonstrates that the proportion of days with a high, or greater than high, fire danger rating is markedly increased during El Niño episodes. More importantly, this study also shows that the already significantly enhanced fire danger associated with El Niño events was even further increased during El Niño events that occurred when the IPO was negative. The potential to use simple indices of climate variability to predict forest fire risk is therefore demonstrated to be significant.


2021 ◽  
Author(s):  
Hui Xu ◽  
Lei Chen ◽  
Wansuo Duan

AbstractThe optimally growing initial errors (OGEs) of El Niño events are found in the Community Earth System Model (CESM) by the conditional nonlinear optimal perturbation (CNOP) method. Based on the characteristics of low-dimensional attractors for ENSO (El Niño Southern Oscillation) systems, we apply singular vector decomposition (SVD) to reduce the dimensions of optimization problems and calculate the CNOP in a truncated phase space by the differential evolution (DE) algorithm. In the CESM, we obtain three types of OGEs of El Niño events with different intensities and diversities and call them type-1, type-2 and type-3 initial errors. Among them, the type-1 initial error is characterized by negative SSTA errors in the equatorial Pacific accompanied by a negative west–east slope of subsurface temperature from the subsurface to the surface in the equatorial central-eastern Pacific. The type-2 initial error is similar to the type-1 initial error but with the opposite sign. The type-3 initial error behaves as a basin-wide dipolar pattern of tropical sea temperature errors from the sea surface to the subsurface, with positive errors in the upper layers of the equatorial eastern Pacific and negative errors in the lower layers of the equatorial western Pacific. For the type-1 (type-2) initial error, the negative (positive) temperature errors in the eastern equatorial Pacific develop locally into a mature La Niña (El Niño)-like mode. For the type-3 initial error, the negative errors in the lower layers of the western equatorial Pacific propagate eastward with Kelvin waves and are intensified in the eastern equatorial Pacific. Although the type-1 and type-3 initial errors have different spatial patterns and dynamic growing mechanisms, both cause El Niño events to be underpredicted as neutral states or La Niña events. However, the type-2 initial error makes a moderate El Niño event to be predicted as an extremely strong event.


2021 ◽  
Author(s):  
Shouwen Zhang ◽  
Hui Wang ◽  
Hua Jiang ◽  
Wentao Ma

AbstractThe late spring rainfall may account for 15% of the annual total rainfall, which is crucial to early planting in southeastern China. A better understanding of the precipitation variations in the late spring and its predictability not only greatly increase our knowledge of related mechanisms, but it also benefits society and the economy. Four models participating in the North American Multi-Model Ensemble (NMME) were selected to study their abilities to forecast the late spring rainfall over southeastern China and the major sources of heavy rainfall from the perspective of the sea surface temperature (SST) field. We found that the models have better abilities to forecast the heavy rainfall over the middle and lower reaches of the Yangtze River region (MLYZR) with only a 1-month lead time, but they failed for a 3-month lead time since the occurrence of the heavy rainfall was inconsistent with the observations. The observations indicate that the warm SST anomalies in the tropical eastern Indian Ocean are vital to the simultaneously heavy rainfall in the MLYZR in May, but an El Niño event is not a necessary condition for determining the heavy rainfall over the MLYZR. The heavy rainfall over the MLYZR in May is always accompanied by warming of the northeastern Indian Ocean and of the northeastern South China Sea (NSCS) from April to May in the models and observations, respectively. In the models, El Niño events may promote the warming processes over the northeastern Indian Ocean, which leads to heavy rainfall in the MLYZR. However, in the real world, El Niño events are not the main reason for the warming of the NSCS, and further research on the causes of this warming is still needed.


2015 ◽  
Vol 28 (19) ◽  
pp. 7561-7575 ◽  
Author(s):  
Yoo-Geun Ham ◽  
Yerim Jeong ◽  
Jong-Seong Kug

Abstract This study uses archives from phase 5 of the Coupled Model Intercomparison Project (CMIP5) to investigate changes in independency between two types of El Niño events caused by greenhouse warming. In the observations, the independency between cold tongue (CT) and warm pool (WP) El Niño events is distinctively increased in recent decades. The simulated changes in independency between the two types of El Niño events according to the CMIP5 models are quite diverse, although the observed features are simulated to some extent in several climate models. It is found that the climatological change after global warming is an essential factor in determining the changes in independency between the two types of El Niño events. For example, the independency between these events is increased after global warming when the climatological precipitation is increased mainly over the equatorial central Pacific. This climatological precipitation increase extends convective response to the east, particularly for CT El Niño events, which leads to greater differences in the spatial pattern between the two types of El Niño events to increase the El Niño independency. On the contrary, in models with decreased independency between the two types of El Niño events after global warming, climatological precipitation is increased mostly over the western Pacific. This confines the atmospheric response to the western Pacific in both El Niño events; therefore, the similarity between them is increased after global warming. In addition to the changes in the climatological state after global warming, a possible connection of the changes in the El Niño independency with the historical mean state is discussed in this paper.


Atmosphere ◽  
2021 ◽  
Vol 12 (7) ◽  
pp. 851
Author(s):  
Gen Li ◽  
Zhiyuan Zhang ◽  
Bo Lu

Under increased greenhouse gas (GHG) forcing, climate models tend to project a warmer sea surface temperature in the eastern equatorial Pacific than in the western equatorial Pacific. This El Niño-like warming pattern may induce an increase in the projected occurrence frequency of extreme El Niño events. The current models, however, commonly suffer from an excessive westward extension of the equatorial Pacific cold tongue accompanied by insufficient equatorial western Pacific precipitation. By comparing the Representative Concentration Pathway (RCP) 8.5 experiments with the historical simulations based on the Coupled Model Intercomparison Project phase 5 (CMIP5), a “present–future” relationship among climate models was identified: models with insufficient equatorial western Pacific precipitation error would have a weaker mean El Niño-like warming pattern as well as a lower increase in the frequency of extreme El Niño events under increased GHG forcing. Using this “present–future” relationship and the observed precipitation in the equatorial western Pacific, this study calibrated the climate projections in the tropical Pacific. The corrected projections showed a stronger El Niño-like pattern of mean changes in the future, consistent with our previous study. In particular, the projected increased occurrence of extreme El Niño events under RCP 8.5 forcing are underestimated by 30–35% in the CMIP5 multi-model ensemble before the corrections. This implies an increased risk of the El Niño-related weather and climate disasters in the future.


2018 ◽  
Vol 99 (1) ◽  
pp. S91-S96 ◽  
Author(s):  
Chris Funk ◽  
Frank Davenport ◽  
Laura Harrison ◽  
Tamuka Magadzire ◽  
Gideon Galu ◽  
...  

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