Empirical evidence of El Niño–Southern Oscillation influence on land surface phenology and productivity in the western United States

Dannenberg, Matthew P.; Song, Conghe; Hwang, Taewon; Wise, Erika K.

doi:10.1016/j.rse.2014.11.026

Cited by 50 publications

(37 citation statements)

References 89 publications

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“…To reduce noise in the ecoregion‐level NDVI time series, we applied outlier and modified best index slope extraction filters (Dannenberg, Song, Hwang, & Wise, ; Hwang, Song, Bolstad, & Band, ; Hwang, Song, Vose, & Band, ), discarded any ecoregion‐level NDVI time series without significant power at annual frequencies using a wavelet filter (Torrence & Compo, ), and smoothed the annual NDVI time series using a difference logistic function (Dannenberg et al., ; Fisher, Mustard, & Vadeboncoeur, ; Hwang, Song, Vose, et al., ; Hwang, Song, Bolstad, et al., ):

\overset{false^}{y} false(t false) = c \times (\frac{1}{1 + e^{a + b t}} - \frac{1}{1 + e^{a^{'} + b^{'} t}}) + d,

…”

Section: Methodsmentioning

confidence: 99%

Shifting Pacific storm tracks as stressors to ecosystems of western North America

Dannenberg

Wise

2017

Global Change Biology

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Much of the precipitation delivered to western North America arrives during the cool season via midlatitude Pacific storm tracks, which may experience future shifts in response to climate change. Here, we assess the sensitivity of the hydroclimate and ecosystems of western North America to the latitudinal position of cool-season Pacific storm tracks. We calculated correlations between storm track variability and three hydroclimatic variables: gridded cool-season standardized precipitation-evapotranspiration index, April snow water equivalent, and water year streamflow from a network of USGS stream gauges. To assess how historical storm track variability affected ecosystem processes, we derived forest growth estimates from a large network of tree-ring widths and land surface phenology and wildfire estimates from remote sensing. From 1980 to 2014, cool-season storm tracks entered western North America between approximately 41°N and 53°N. Cool-season moisture supply and snowpack responded strongly to storm track position, with positive correlations to storm track latitude in eastern Alaska and northwestern Canada but negative correlations in the northwestern U.S. Ecosystems of the western United States were greener and more productive following winters with south-shifted storm tracks, while Canadian ecosystems were greener in years when the cool-season storm track was shifted to the north. On average, larger areas of the northwestern United States were burned by moderate to high severity wildfires when storm tracks were displaced north, and the average burn area per fire also tended to be higher in years with north-shifted storm tracks. These results suggest that projected shifts of Pacific storm tracks over the 21st century would likely alter hydroclimatic and ecological regimes in western North America, particularly in the northwestern United States, where moisture supply and ecosystem processes are highly sensitive to the position of cool-season storm tracks.

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\overset{false^}{y} false(t false) = c \times (\frac{1}{1 + e^{a + b t}} - \frac{1}{1 + e^{a^{'} + b^{'} t}}) + d,

…”

Section: Methodsmentioning

confidence: 99%

Shifting Pacific storm tracks as stressors to ecosystems of western North America

Dannenberg

Wise

2017

Global Change Biology

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“…For urban vegetation, a difference logistic function with six parameters was used to characterize the mean phenology at each pixel [21,22,24,30,47]:…”

Section: Mean Phenology Models For Urban Vegetationmentioning

confidence: 99%

“…Equation (1) was fitted at each urban vegetation pixel using an iteratively-weighted, nonlinear least squares regression [21,48]. SOS and EOS of urban vegetation are defined as the dates when EV I(t) reached the inflection points of the fitted curve in the spring rising and autumn falling periods of EVI time series [21,30].…”

Section: Mean Phenology Models For Urban Vegetationmentioning

confidence: 99%

“…Remote sensing observations offer consistent quantitative measurements of land surface properties, making long-term satellite observations ideal resources for monitoring vegetation phenology [19]. Many algorithms have been developed to estimate phenological metrics based on time series of vegetation indices derived from Advanced Very High Resolution Radiometer (AVHRR) and Moderate Resolution Imaging Spectroradiometer (MODIS) [20][21][22][23][24][25]. More specifically, studies have reported an increase of 7.6 days in the length of growing season (LOS) caused by urbanization in the Eastern United States [26].…”

Section: Introductionmentioning

confidence: 99%

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Impacts of Urbanization on Vegetation Phenology over the Past Three Decades in Shanghai, China

Qiu

Song

2017

Remote Sensing

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Vegetation phenology manifests the rhythm of annual plant life activities. It has been extensively studied in natural ecosystems. However, major knowledge gaps still exist in understanding the impacts of urbanization on vegetation phenology. This study addresses two questions to fill the knowledge gaps: (1) How does vegetation phenology vary spatially and temporally along a rural-to-urban transect in Shanghai, China, over the past three decades? (2) How do landscape composition and configuration affect those variations of vegetation phenology? To answer these questions, 30 m × 30 m mean vegetation phenology metrics, including the start of growing season (SOS), end of growing season (EOS), and length of growing season (LOS), were derived for urban vegetation using dense stacks of enhanced vegetation index (EVI) time series from images collected by Landsat 5-8 satellites from 1984 to 2015. Landscape pattern metrics were calculated using high spatial resolution aerial photos. We then used Pearson correlation analysis to quantify the associations between phenology patterns and landscape metrics. We found that vegetation in urban centers experienced advances of SOS for 5-10 days and delays of EOS for 5-11 days compared with those located in the surrounding rural areas. Additionally, we observed strong positive correlations between landscape composition (percentage of landscape area) of developed land and LOS of urban vegetation. We also found that the landscape configuration of local land cover types, especially patch density and edge density, was significantly correlated with the spatial patterns of vegetation phenology. These results demonstrate that vegetation phenology in the urban area is significantly different from its rural surroundings. These findings have implications for urban environmental management, ranging from biodiversity protection to public health risk reduction.

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“…In the northwestern limit of TDFs, the summer monsoon represents the most important water source in the region and determines biological activity and ecosystem fluxes [Campo et al, 1998;Pérez-Ruiz et al, 2010;Forzieri et al, 2014]. Moreover, this region is susceptible to El Niño-Southern Oscillation that impacts winter precipitation which has been linked to the subsequent summer monsoon [Zhu et al, 2007;Mahmood and Vivoni, 2014;Dannenberg et al, 2015].…”

Section: Introductionmentioning

confidence: 99%

Variations of net ecosystem production due to seasonal precipitation differences in a tropical dry forest of northwest Mexico

et al. 2015

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Due to their large extent and high primary productivity, tropical dry forests (TDF) are important contributors to atmospheric carbon exchanges in subtropical and tropical regions. In northwest Mexico, a bimodal precipitation regime that includes winter precipitation derived from Pacific storms and summer precipitation from the North American monsoon (NAM) couples water availability with ecosystem processes. We investigated the net ecosystem production of a TDF ecosystem using a 4.5 year record of water and carbon fluxes obtained from the eddy covariance method complemented with remotely sensed data. We identified a large CO2 efflux at the start of the summer season that is strongly related to the preceding winter precipitation and greenness. Since this CO2 efflux occurs prior to vegetation green‐up, we infer that respiration is mainly due to decomposition of soil organic matter accumulated from the prior growing season. Overall, ecosystem respiration has an important effect on the net ecosystem production but can be overwhelmed by the strength of the primary productivity during the NAM. Precipitation characteristics during NAM have significant controls on sustaining carbon fixation in the TDF into the fall season. We identified that a threshold of ~350 to 400 mm of monsoon precipitation leads to a switch in the annual carbon balance in the TDF ecosystem from a net source (+102 g C/m2/yr) to a net sink (−249 g C/m2/yr). This monsoonal precipitation threshold is typically exceeded one out of every 2 years. The close coupling of winter and summer periods with respect to carbon fluxes suggests that the annual carbon balance is dependent on precipitation amounts in both seasons in TDF ecosystems.

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Empirical evidence of El Niño–Southern Oscillation influence on land surface phenology and productivity in the western United States

Cited by 50 publications

References 89 publications

Shifting Pacific storm tracks as stressors to ecosystems of western North America

Shifting Pacific storm tracks as stressors to ecosystems of western North America

Impacts of Urbanization on Vegetation Phenology over the Past Three Decades in Shanghai, China

Variations of net ecosystem production due to seasonal precipitation differences in a tropical dry forest of northwest Mexico

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