Effects of ENSO-linked climate and vegetation on population dynamics of sympatric rodent species in semiarid grasslands of Inner Mongolia, China

2011 ◽  
Vol 89 (8) ◽  
pp. 678-691 ◽  
Author(s):  
G. Jiang ◽  
T. Zhao ◽  
J. Liu ◽  
L. Xu ◽  
G. Yu ◽  
...  
Keyword(s):  
El Niño ◽  
Inner Mongolia ◽  
Vegetation Index ◽  
El Nino ◽  
Southern Oscillation ◽  
Time Lag ◽  
Rodent Species ◽  
Bottom Up ◽  
Precipitation Temperature ◽  
Rodent Abundance

El Niño Southern Oscillation (ENSO) linked climate has been known to be associated with several rodent species, but its effects on rodent community at both spatial and temporal scales are not well studied. In this study, we investigated the possible causal chain relating ENSO, precipitation, temperature, and vegetation index (normalized difference vegetation index, NDVI) to rodent abundance for 14 sympatric rodent species in 21 counties of semiarid grasslands in Inner Mongolia, China, from 1982 to 2006. We found that both precipitation and temperature showed a generally direct positive effect on rodent abundance in many species in the current year, but indirect effects that operate through NDVI in the current or following year could have a reverse effect on abundance. We described one ENSO-linked precipitation bottom-up chain and three ENSO-linked temperature bottom-up chains. These observed bottom-up links reveal that in El Niño years, or 1 year after La Niña years, or 2 years after El Niño years, ENSO-driven climate or vegetation factors tend to increase population abundances of many sympatric rodent species in this region. We also found time-lag effects and the life-history strategy (i.e., functional groups of hibernating behavior, activity rhythm, or food habits) also contribute to the observed complicated effects of SOI on precipitation, temperature, NDVI, and ultimately rodent abundance.

scholarly journals Drought risk in the Bolivian Altiplano associated with El Niño Southern Oscillation using satellite imagery data

2019 ◽  
Author(s):  
Claudia Canedo-Rosso ◽  
Stefan Hochrainer-Stigler ◽  
Georg Pflug ◽  
Bruno Condori ◽  
Ronny Berndtsson
Keyword(s):  
Satellite Imagery ◽  
El Niño ◽  
Crop Production ◽  
Vegetation Index ◽  
Crop Yields ◽  
El Nino ◽  
Southern Oscillation ◽  
Drought Risk ◽  
Bolivian Altiplano ◽  
Imagery Data

Abstract. Drought is a major natural hazard in the Bolivian Altiplano that causes large losses to farmers, especially during positive ENSO phases. However, empirical data for drought risk estimation purposes are scarce and spatially uneven distributed. Due to these limitations, similar to many other regions in the world, we tested the performance of satellite imagery data for providing precipitation and temperature data. The results show that droughts can be better predicted using a combination of satellite imagery and ground-based available data. Consequently, the satellite climate data were associated with the Normalized Difference Vegetation Index (NDVI) in order to evaluate the crop production variability. Moreover, NDVI was used to target specific drought hotspot regions. Furthermore, during positive ENSO phase (El Niño years), a significant decrease in crop yields can be expected and we indicate areas where losses will be most pronounced. The results can be used for emergency response operations and enable a pro-active approach to disaster risk management against droughts. This includes economic-related and risk reduction strategies such as insurance and irrigation.

scholarly journals Anomalías de vegetación asociadas con el fenómeno del ENOS en el valle geográfico del río Cauca, Colombia

2017 ◽  
pp. 89 ◽  
Author(s):  
J. M. Valencia ◽  
C. E. García ◽  
D. Montero
Keyword(s):  
El Niño ◽  
Vegetation Index ◽  
El Nino ◽  
Southern Oscillation ◽  
Temporal Analysis ◽  
La Niña ◽  
Agricultural Crop ◽  
Factors Affecting ◽  
La Nina ◽  
The Impact

<p>The main factors affecting the production and yield of sugarcane are variety, agronomic management, soil type and climate, of which the first three there is some control, while the climate is one factor of which you cannot have any control, therefore, it should be monitored. Colombia, being located in the equatorial pacific, is affected by two atmospheric oceanic phenomena known as “El Niño” and “La Niña”, which make up the climatic phenomenon of ENSO (El Niño-Southern Oscillation) and affect the quantity and the number of days with rainfall and influences the production of sugarcane. The objective of this work is to identify spatially and temporally the zones with greater and lower impact of the ENSO phenomenon in the cultivation of sugarcane in Colombia through the use of the Standard Vegetation Index (SVI) and the Rainfall Anomally Index (RAI) using EVI/MODIS images and precipitation data from meteorological stations on a quarterly basis for the period 2000-2015. A similar trend was found between both indices in the “El Niño” and “Neutral” seasons, while in the “La Niña” season the RAI tended to rise while the SVI decreased when the RAI was very high, this tendency being much more marked in areas with floods caused by the overflow of the main rivers. In addition, a comparison was made between the SVI index and a productivity anomaly index (IAP), finding a direct correlation between both (R<sup>2</sup> = 0.4, p&lt;0.001). This work showed that through the use of vegetation indexes, a temporal analysis of the impact of climate on an agricultural crop can be carried out, especially with ENSO conditions.</p>

scholarly journals El Niño/Southern Oscillation-driven rainfall pulse amplifies predation by owls on seabirds via apparent competition with mice

2018 ◽  
Vol 285 (1889) ◽  
pp. 20181161 ◽  
Author(s):  
Sarah K. Thomsen ◽  
David M. Mazurkiewicz ◽  
Thomas R. Stanley ◽  
David J. Green
Keyword(s):  
El Niño ◽  
Species Interactions ◽  
El Nino ◽  
Southern Oscillation ◽  
El Niño Southern Oscillation ◽  
El Nino Southern Oscillation ◽  
Bottom Up ◽  
Mouse Population ◽  
Resource Pulses ◽  
Rainfall Pulse

Most approaches for assessing species vulnerability to climate change have focused on direct impacts via abiotic changes rather than indirect impacts mediated by changes in species interactions. Changes in rainfall regimes may influence species interactions from the bottom-up by increasing primary productivity in arid environments, but subsequently lead to less predictable top-down effects. Our study demonstrates how the effects of an EL Niño/Southern Oscillation (ENSO)-driven rainfall pulse ricochets along a chain of interactions between marine and terrestrial food webs, leading to enhanced predation of a vulnerable marine predator on its island breeding grounds. On Santa Barbara Island, barn owls ( Tyto alba ) are the main predator of a nocturnal seabird, the Scripps's murrelet ( Synthliboramphus scrippsi ), as well as an endemic deer mouse. We followed the links between rainfall, normalized difference vegetation index and subsequent peaks in mouse and owl abundance. After the mouse population declined steeply, there was approximately 15-fold increase in the number of murrelets killed by owls. We also simulated these dynamics with a mathematical model and demonstrate that bottom-up resource pulses can lead to subsequent declines in alternative prey. Our study highlights the need for understanding how species interactions will change with shifting rainfall patterns through the effects of ENSO under global change.

scholarly journals Spatial Patterns of NDVI Variation over Indonesia and Their Relationship to ENSO Warm Events during the Period 1982–2006

2009 ◽  
Vol 22 (24) ◽  
pp. 6612-6623 ◽  
Author(s):  
Stefan Erasmi ◽  
Pavel Propastin ◽  
Martin Kappas ◽  
Oleg Panferov
Keyword(s):  
Time Series ◽  
El Niño ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
El Nino ◽  
Southern Oscillation ◽  
Spatially Explicit ◽  
Forest Conversion ◽  
Climate Anomalies ◽  
Indonesian Archipelago

Abstract The present study is based on the assumption that vegetation in Indonesia is significantly affected by climate anomalies that are related to El Niño–Southern Oscillation (ENSO) warm phases (El Niño) during the past decades. The analysis builds upon a monthly time series from the normalized difference vegetation index (NDVI) gridded data from the Advanced Very High Resolution Radiometer (AVHRR) and two ENSO proxies, namely, sea surface temperature anomalies (SSTa) and Southern Oscillation index (SOI), and aims at the analysis of the spatially explicit dimension of ENSO impact on vegetation on the Indonesian archipelago. A time series correlation analysis between NDVI anomalies and ENSO proxies for the most recent ENSO warm events (1982–2006) showed that, in general, anomalies in vegetation productivity over Indonesia can be related to an anomalous increase of SST in the eastern equatorial Pacific and to decreases in SOI, respectively. The net effect of these variations is a significant decrease in NDVI values throughout the affected areas during the ENSO warm phases. The 1982/83 ENSO warm episode was rather short but—in terms of ENSO indices—the most extreme one within the study period. The 1997/98 El Niño lasted longer but was weaker. Both events had significant impact on vegetation in terms of negative NDVI anomalies. Compared to these two major warm events, the other investigated events (1987/88, 1991/92, 1994/95, and 2002/03) had no significant effect on vegetation in the investigated region. The land cover–type specific sensitivity of vegetation to ENSO anomalies revealed thresholds of vegetation response to ENSO warm events. The results for the 1997/98 ENSO warm event confirm the hypothesis that the vulnerability of vegetated tropical land surfaces to drought conditions is considerably affected by land use intensity. In particular, it could be shown that natural forest areas are more resistant to drought stress than degraded forest areas or cropland. Comparing the spatially explicit patterns of El Niño–related vegetation variation during the major El Niño phases, the spatial distribution of affected areas reveals distinct core regions of ENSO drought impact on vegetation for Indonesia that coincide with forest conversion and agricultural intensification hot spots.

scholarly journals Shifts in Growing Season of Tropical Deciduous Forests as Driven by El Niño and La Niña during 2001–2016

Forests ◽  
2018 ◽  
Vol 9 (8) ◽  
pp. 448 ◽  
Author(s):  
Phan Diem ◽  
Uday Pimple ◽  
Asamaporn Sitthi ◽  
Pariwate Varnakovida ◽  
Katsunori Tanaka ◽  
...  
Keyword(s):  
El Niño ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Deciduous Forest ◽  
El Nino ◽  
Southern Oscillation ◽  
Growing Season ◽  
La Niña ◽  
Tropical Deciduous Forest ◽  
La Nina

This study investigated the spatiotemporal dynamics of tropical deciduous forest including dry dipterocarp forest (DDF) and mixed deciduous forest (MDF) and its phenological changes in responses to El Niño and La Niña during 2001–2016. Based on time series of Normalized Difference Vegetation Index (NDVI) extracted from Moderate Resolution Imaging Spectroradiometer (MODIS), the start of growing season (SOS), the end of growing season (EOS), and length of growing season (LOS) were derived. In absence of climatic fluctuation, the SOS of DDF commonly started on 106 ± 7 DOY, delayed to 132 DOY in El Niño year (2010) and advanced to 87 DOY in La Niña year (2011). Thus, there was a delay of about 19 to 33 days in El Niño and an earlier onset of about 13 to 27 days in La Niña year. The SOS of MDF started almost same time as of DDF on the 107 ± 7 DOY during the neutral years and delayed to 127 DOY during El Niño, advanced to 92 DOY in La Niña year. The SOS of MDF was delayed by about 12 to 28 days in El Niño and was earlier about 8 to 22 days in La Niña. Corresponding to these shifts in SOS and LOS of both DDF and MDF were also induced by the El Niño–Southern Oscillation (ENSO).

scholarly journals Time Series Analysis of MODIS-Derived NDVI for the Hluhluwe-Imfolozi Park, South Africa: Impact of Recent Intense Drought

Climate ◽  
2018 ◽  
Vol 6 (4) ◽  
pp. 95 ◽  
Author(s):  
Nkanyiso Mbatha ◽  
Sifiso Xulu
Keyword(s):  
El Niño ◽  
Vegetation Index ◽  
El Nino ◽  
Southern Oscillation ◽  
Climatic Variability ◽  
Phase Relationship ◽  
Google Earth ◽  
Area Index ◽  
Mk Test ◽  
Significant Downward Trend

The variability of temperature and precipitation influenced by El Niño-Southern Oscillation (ENSO) is potentially one of key factors contributing to vegetation product in southern Africa. Thus, understanding large-scale ocean–atmospheric phenomena like the ENSO and Indian Ocean Dipole/Dipole Mode Index (DMI) is important. In this study, 16 years (2002–2017) of Moderate Resolution Imaging Spectroradiometer (MODIS) Terra/Aqua 16-day normalized difference vegetation index (NDVI), extracted and processed using JavaScript code editor in the Google Earth Engine (GEE) platform was used to analyze the vegetation response pattern of the oldest proclaimed nature reserve in Africa, the Hluhluwe-iMfolozi Park (HiP) to climatic variability. The MODIS enhanced vegetation index (EVI), burned area index (BAI), and normalized difference infrared index (NDII) were also analyzed. The study used the Modern Retrospective Analysis for the Research Application (MERRA) model monthly mean soil temperature and precipitations. The Global Land Data Assimilation System (GLDAS) evapotranspiration (ET) data were used to investigate the HiP vegetation water stress. The region in the southern part of the HiP which has land cover dominated by savanna experienced the most impact of the strong El Niño. Both the HiP NDVI inter-annual Mann–Kendal trend test and sequential Mann–Kendall (SQ-MK) test indicated a significant downward trend during the El Niño years of 2003 and 2014–2015. The SQ-MK significant trend turning point which was thought to be associated with the 2014–2015 El Niño periods begun in November 2012. The wavelet coherence and coherence phase indicated a positive teleconnection/correlation between soil temperatures, precipitation, soil moisture (NDII), and ET. This was explained by a dominant in-phase relationship between the NDVI and climatic parameters especially at a period band of 8–16 months.

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