Spatial patterns and temporal dynamics in savanna vegetation phenology across the North Australian Tropical Transect

Ma, Xuanlong; Huete, Alfredo; Yu, Qiang; Restrepo‐Coupe, Natalia; Davies, Kevin; Broich, Mark; Ratana, P.; Beringer, Jason; Hutley, Lindsay B.; Cleverly, James; Boulain, N.; Eamus, Derek

doi:10.1016/j.rse.2013.07.030

Cited by 194 publications

(204 citation statements)

References 83 publications

Supporting

Mentioning

191

Contrasting

Order By: Relevance

“…Changes in maximum daily trunk shrinkage arising from reduced water availability occur earlier and stronger than changes in stomatal conductance, stem water potential or transpiration (Ortuno et al, 2006;Conejero et al, 2007Conejero et al, , 2011Galindo et al, 2013). Nonetheless, rates of sap flow declined with maximum daily stem shrinkage, both of which responded exponentially to changes in depth-to-groundwater (Ma et al, 2013). Similarly, February et al (2007) and Drake et al (2013) found that increased groundwater supply (actual or simulated) resulted in increased stem increment, sap flow and xylem water potential.…”

Section: Effects Of Groundwater On Growth and Dendrochronological Traitsmentioning

confidence: 95%

“…phenology, LAI) and function (e.g. ET, gross primary productivity) has become increasingly sophisticated (Glenn et al, 2010;Yuan et al, 2010;Jung et al, 2011;Rossini et al, 2012;Kanniah et al, 2013;Ma et al, 2013;Nagler et al, 2013) and increasingly applied to realworld applications of water resources management (Scott et al, 2008;Glenn et al, 2010;Barron et al, 2014;Doody et al, 2014). Remote sensing (RS) provides a robust and spatially explicit means to assess not only vegetation structure and function but also relationships amongst these and climate variables.…”

Section: Satellite-based Approachesmentioning

confidence: 99%

See 1 more Smart Citation

Groundwater-dependent ecosystems: recent insights from satellite and field-based studies

Eamus

Zolfaghar

Villalobos‐Vega

et al. 2015

Hydrol. Earth Syst. Sci.

130

112

View full text Add to dashboard Cite

Abstract. Groundwater-dependent ecosystems (GDEs) are at risk globally due to unsustainable levels of groundwater extraction, especially in arid and semi-arid regions. In this review, we examine recent developments in the ecohydrology of GDEs with a focus on three knowledge gaps: (1) how do we locate GDEs, (2) how much water is transpired from shallow aquifers by GDEs and (3) what are the responses of GDEs to excessive groundwater extraction? The answers to these questions will determine water allocations that are required to sustain functioning of GDEs and to guide regulations on groundwater extraction to avoid negative impacts on GDEs.We discuss three methods for identifying GDEs: (1) techniques relying on remotely sensed information; (2) fluctuations in depth-to-groundwater that are associated with diurnal variations in transpiration; and (3) stable isotope analysis of water sources in the transpiration stream.We then discuss several methods for estimating rates of GW use, including direct measurement using sapflux or eddy covariance technologies, estimation of a climate wetness index within a Budyko framework, spatial distribution of evapotranspiration (ET) using remote sensing, groundwater modelling and stable isotopes. Remote sensing methods often rely on direct measurements to calibrate the relationship between vegetation indices and ET. ET from GDEs is also determined using hydrologic models of varying complexity, from the White method to fully coupled, variable saturation models. Combinations of methods are typically employed to obtain clearer insight into the components of groundwater discharge in GDEs, such as the proportional importance of transpiration versus evaporation (e.g. using stable isotopes) or from groundwater versus rainwater sources.Groundwater extraction can have severe consequences for the structure and function of GDEs. In the most extreme cases, phreatophytes experience crown dieback and death following groundwater drawdown. We provide a brief review of two case studies of the impacts of GW extraction and then provide an ecosystem-scale, multiple trait, integrated metric of the impact of differences in groundwater depth on the structure and function of eucalypt forests growing along a natural gradient in depth-to-groundwater. We conclude with a discussion of a depth-to-groundwater threshold in this mesic GDE. Beyond this threshold, significant changes occur in ecosystem structure and function.

show abstract

Section: Effects Of Groundwater On Growth and Dendrochronological Traitsmentioning

confidence: 95%

Section: Satellite-based Approachesmentioning

confidence: 99%

Groundwater-dependent ecosystems: recent insights from satellite and field-based studies

Eamus

Zolfaghar

Villalobos‐Vega

et al. 2015

Hydrol. Earth Syst. Sci.

130

112

View full text Add to dashboard Cite

show abstract

“…Vegetation indices also seem to respond clearly to severe droughts (Wagle et al 2014). In tropical savannas, the Enhanced Vegetation Index (EVI) is correlated to ground measurements of GEP (Xuanlong et al 2013).…”

Section: Introductionmentioning

confidence: 99%

How Strong Is the Relationship Between Rainfall Variability and Caatinga Productivity? A Case Study Under a Changing Climate

Salimon

Anderson

2018

An. Acad. Bras. Ciênc.

View full text Add to dashboard Cite

Despite the knowledge of the influence of rainfall on vegetation dynamics in semiarid tropical Brazil, few studies address and explore quantitatively the various aspects of this relationship. Moreover, Northeast Brazil is expected to have its rainfall reduced by as much as 60% until the end of the 21 st Century, under scenario AII of the IPCC Report 2010. We sampled and analyzed satellite-derived monthly rainfall and a vegetation index data for 40 sites with natural vegetation cover in Paraíba State, Brazil from 2001 to 2012. In addition, the anomalies for both variables were calculated. Rainfall variation explained as much as 50% of plant productivity, using the vegetation index as a proxy, and rainfall anomaly explained 80% of the vegetation productivity anomaly. In an extreme dry year (2012), with 65% less rainfall than average for the period 2001-2012, the vegetation index decreased by 25%. If such decrease persists in a long term trend in rainfall reduction, this could lead to a disruption in this ecosystem functioning and the dominant vegetation could become even more xeric or desert-like, bringing serious environmental, social and economical impacts.

show abstract

“…There was also a positive and significant relation between the passive microwave indices and gross ecosystem productivity (GEP) calculated from flux tower data (Table 3). At the Howard Springs tropical woody savanna site, the EVI seasonal signal responded to and was synchronous with the arrival of the monsoonal rains during the spring-summer transition [Ma et al, 2013]. Since higher FI and PI values were present during the rainy season (austral summer precipitation) and the biomass of this site was moderate, a consistent explanation of the observed FI and PI trends could be related to a significant contribution of soil to overall emissivity.…”

Section: Seasonal Patterns Of Passive Microwave Indicesmentioning

confidence: 63%

“…Interestingly, PI values of both sites showed an inverse trend with MODIS EVI and LAI, resulting in significant and negative relation with EVI and LAI (Table 3). At Alice Springs, this could be due to a prolonged vegetation drying phase from 2007 to 2008 as reported by Ma et al [2013] (Figure 4). By contrast, at Sturt Plains, the temporal trend of PI was more complex.…”

Section: Seasonal Patterns Of Passive Microwave Indicesmentioning

confidence: 65%

Behavior of multitemporal and multisensor passive microwave indices in Southern Hemisphere ecosystems

et al. 2014

Self Cite

View full text Add to dashboard Cite

This study focused on the time series analysis of passive microwave and optical satellite data collected from six Southern Hemisphere ecosystems in Australia and Argentina. The selected ecosystems represent a wide range of land cover types, including deciduous open forest, temperate forest, tropical and semiarid savannas, and grasslands. We used two microwave indices, the frequency index (FI) and polarization index (PI), to assess the relative contributions of soil and vegetation properties (moisture and structure) to the observations. Optical-based satellite vegetation products from the Moderate Resolution Imaging Spectroradiometer were also included to aid in the analysis. We studied the X and Ka bands of the Advanced Microwave Scanning Radiometer-EOS and Wind Satellite, resulting in up to four observations per day (1:30, 6:00, 13:30, and 18:00 h). Both the seasonal and hourly variations of each of the indices were examined. Environmental drivers (precipitation and temperature) and eddy covariance measurements (gross ecosystem productivity and latent energy) were also analyzed. It was found that in moderately dense forests, FI was dependent on canopy properties (leaf area index and vegetation moisture). In tropical woody savannas, a significant regression (R 2 ) was found between FI and PI with precipitation (R 2 > 0.5) and soil moisture (R 2 > 0.6). In the areas of semiarid savanna and grassland ecosystems, FI variations found to be significantly related to soil moisture (R 2 > 0.7) and evapotranspiration (R 2 > 0.5), while PI varied with vegetation phenology. Significant differences (p < 0.01) were found among FI values calculated at the four local times.

show abstract

Spatial patterns and temporal dynamics in savanna vegetation phenology across the North Australian Tropical Transect

Cited by 194 publications

References 83 publications

Groundwater-dependent ecosystems: recent insights from satellite and field-based studies

Groundwater-dependent ecosystems: recent insights from satellite and field-based studies

How Strong Is the Relationship Between Rainfall Variability and Caatinga Productivity? A Case Study Under a Changing Climate

Behavior of multitemporal and multisensor passive microwave indices in Southern Hemisphere ecosystems

Contact Info

Product

Resources

About